OJUS LLC’s Post

#linkedinconnection #linkedinfamily #hiringimmediately Data Engineer with AWS Redshit (Mandatory) Harrisburgh, PA Onsite H4EAD/GC-EAD/GC/USC 12 Months C2C Send Resumes to mark@vitconsystems.com for immediate response. As an AWS Redshift Data Engineer, the primary responsibility is to design, implement, and maintain data solutions using Amazon Redshift. The ideal candidate should possess the following skills: Data Modeling and Design: Develop and maintain data models for Redshift databases, including schema design, table structures, and optimization techniques. Collaborate with data architects and stakeholders to understand requirements and translate them into efficient data structures. ETL Development: Design and implement Extract, Transform, Load (ETL) processes to extract data from various sources, transform it as per business requirements, and load it into Redshift. Develop efficient and scalable ETL workflows, considering data quality, performance, and data governance. Performance Optimization: Optimize query performance by creating appropriate data distribution keys, sort keys, and compression techniques. Identify and resolve performance bottlenecks, fine-tune queries, and optimize data processing to enhance Redshift's performance. Data Integration: Integrate Redshift with other AWS services, such as AWS Glue, AWS Lambda, Amazon S3, and more, to build end-to-end data pipelines. Ensure seamless data flow between different systems and platforms, maintaining data integrity and consistency. Monitoring and Troubleshooting: Implement monitoring and alerting systems to proactively identify issues and ensure the stability and availability of the Redshift cluster. Perform troubleshooting, diagnose and resolve data-related issues, and work closely with support teams to resolve any performance or operational problems. Security and Compliance: Implement security best practices to protect data stored in Redshift. Ensure compliance with data privacy regulations and industry standards, such as GDPR and HIPAA. Implement encryption, access controls, and data masking techniques to secure sensitive data. Documentation and Collaboration: Maintain documentation of data models, ETL processes, and system configurations. Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and provide data solutions that meet their needs. Scalability and Capacity Planning: Plan and execute strategies for scaling Redshift clusters to handle increasing data volumes and user demands. Monitor resource utilization, track data growth, and make recommendations for capacity planning and infrastructure scaling. Knowledge or previous experience in Oracle PLSQL will be an added advantage. #dataengineer #dataengineerjobs #usitrecruitment #c2crequirements #usitstaffing #immediatehiring #itandsoftware #usaitjobs #corp2corp

THIS IS FOR #W2 NOT FOR #C2C Job Title: Senior Data Engineer Location: [Specify Location] Experience: 8+ Years Job Description: We are looking for a seasoned Senior Data Engineer with over 8 years of experience to lead and drive our data engineering initiatives. As a Senior Data Engineer, you will be responsible for designing, implementing, and maintaining robust data infrastructure while providing technical leadership to the data engineering team. If you have a proven track record of successfully delivering complex data solutions and are passionate about driving innovation in the data space, we encourage you to apply. Responsibilities: Data Architecture and Design: Lead the design and implementation of scalable and efficient data models. Provide expertise in designing and evolving data architecture to meet current and future business needs. Data Integration and ETL: Architect and implement data integration solutions to unify data from diverse sources. Oversee the development of ETL processes to ensure seamless and accurate data flow. Leadership and Mentoring: Provide technical leadership and mentorship to junior data engineers. Collaborate with cross-functional teams and guide them on best practices in data engineering. Optimization and Performance: Big Data Technologies: Leverage expertise in big data technologies, such as Hadoop and Spark, to solve complex data challenges. Stay current with industry trends and incorporate new technologies to improve data solutions. Cloud Platform Expertise: Demonstrate proficiency in cloud platforms (e.g., AWS, Azure, GCP) and utilize cloud services for scalable and flexible data solutions. Data Governance and Compliance: Implement and enforce data governance policies and ensure compliance with data regulations. Work closely with stakeholders to address data quality and security concerns. Collaboration and Communication: Collaborate with cross-functional teams, data scientists, and analysts to understand data requirements. Communicate effectively with both technical and non-technical stakeholders. Qualifications: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. 8+ years of hands-on experience in data engineering roles. Strong expertise in SQL, database management systems, and data modeling. Proficient in programming languages such as Python, Java, or Scala. Experience with big data technologies (Hadoop, Spark) and related ecosystems. In-depth knowledge of ETL tools and processes. Demonstrated leadership and mentoring skills. Familiarity with cloud-based data solutions and services. Excellent problem-solving and analytical skills. Strong communication and interpersonal skills. #DataEngineer #BigData #DataInfrastructure #DataArchitecture #ETL #DataModeling #SQL #DataIntegration #DataPipeline #DataWarehouse #CloudComputing #AWS #Azure #GCP #Hadoop #Spark #Python #Java #Scala

#Hiring for #Data #engineer #c2c #local #12+years Location: Sunnyvale, CA. (Need Local candidates only) on C2C Duration: 12+ Months (Possible Extention) Experience: 12+ Years   Job Description:     What you'll do:  •          You will use cutting edge data engineering techniques to create critical datasets and dig into our mammoth scale of data to help unleash the power of data science by imagining, developing, and maintaining data pipelines that our Data Scientists and Analysts can rely on.  •          You will be responsible for contributing to an orchestration layer of complex data transformations, refining raw data from source into targeted, valuable data assets for consumption in a governed way.  •          You will partner with Data Scientists, Analysts, other engineers, and business stakeholders to solve complex and exciting challenges so that we can build out capabilities that evolve the marketplace business model while making a positive impact on our customers' and sellers’ lives.  •          You will design, develop and maintain highly scalable and fault-tolerant real time, near real time and batch data systems/pipelines that process, store, and serve large volumes of data with optimal performance.  •          You will build business domain knowledge to support the data need for product teams, analytics, data scientists and other data consumers.     What you'll bring:  •          At least 4+ years of experience development of big data technologies/data pipelines   •          Experience with in big data technologies like Hadoop, Apache Spark (Scala preferred), Apache Hive, or similar frameworks on the cloud (GCP preferred, AWS, Azure etc.) to build batch data pipelines with strong focus on optimization, SLA adherence and fault tolerance.  •          Experience in writing SQL to analyze, optimize, profile data preferably in BigQuery or SPARK SQL   •          Strong data modeling skills are necessary for designing a schema that can accommodate the evolution of data sources and facilitate seamless data joins across various datasets.   •          Strong analytical and problem-solving skills are crucial for identifying and resolving issues that may arise during the data integration and schema evolution process.  Nice to have from you:   •          Experience building complex near real time (NRT) streaming data pipelines using Apache Kafka, Spark streaming, Kafka Connect with a strong focus on stability, scalability and SLA adherence.  •          Good understanding of REST APIs – working knowledge on Apache Druid, Redis, Elastic search, GraphQL or similar technologies.  Understanding of API contracts, building telemetry, stress testing etc.   •          Exposure in developing reports/dashboards using Looker/Tableau    Experience in eCommerce domain preferred.now Email-rashmi@linktms.com

Hello Connections, Immediate position open below. Position: ETL Architect Location: Remote Duration: 6+ Months Sub vending allowed: Yes Visa Constraints : None   Data Architecture and Modeling: Design and implement robust, scalable data models to support PMM application, analytics and business intelligence initiatives. Optimize data warehousing solutions and manage data migrations in the AWS ecosystem, utilizing Amazon Redshift, RDS, and DocumentDB services. ETL Development: Develop and maintain scalable ETL pipelines using AWS Glue and other AWS services to enhance data collection, integration, and aggregation. Ensure data integrity and timeliness in the data pipeline, troubleshooting any issues that arise during data processing. Data Integration: Integrate data from various sources using AWS technologies, ensuring seamless data flow across systems. Collaborate with stakeholders to define data ingestion requirements and implement solutions to meet business needs. Performance Optimization: Monitor, tune, and manage database performance to ensure efficient data loads and queries. Implement best practices for data management within AWS to optimize storage and computing costs. Security and Compliance: Ensure all data practices comply with regulatory requirements and department policies. Implement and maintain security measures to protect data within AWS services. Team Collaboration and Leadership: Lead and mentor junior data engineers and team members on AWS best practices and technical challenges. Collaborate with UI/API team, business analysts, and other stakeholders to support data-driven decision-making. Innovation and Continuous Improvement: Explore and adopt new technologies within the AWS cloud to enhance the capabilities of the data platform. Continuously improve existing systems by analyzing business needs and technology trends. Qualifications for  Bachelor’s degree in Computer Science, Computer Engineering or similar. Minimum 5 + years ETL coding experience Proficiency in programming languages such as Python and SQL for data processing and automation Experience with distributed computing frameworks like Apache Spark or similar technologies Experience with AWS data environment, primarily Glue, S3, DocumentDB, Redshift, RDS, Athena, etc. Experience with data warehouses/RDBMS like Redshift and NoSQL data stores such as DocumentDB, DynamoDB, OpenSearch, etc Experience in building data lakes using AWS Lake Formation Experience with workflow orchestration and scheduling tools like AWS Step Functions, AWS MWAA, etc.. Strong understanding of relational databases (including tables, views, indexes, table spaces) Experience with source control tools such as GitHub and related CI/CD processes Ability to analyze a company’s data needs Strong problem-solving skills Experience with the SDLC and Agile methodologies Kindly share updated resume to kavya@intellisofttech.com #etlarchitect #remote #c2cjob #c2crequirement #immediate #hiring #share #vendors

Hi Everyone, We have job opportunity for Senior Data Engineer with one of our clients. Kindly let me know if you are interested or someone who might be interested, please call me or send an updated resume. I can be reached @703-665 5599 x 811 (or) Email: alekya.boda@talteam.com Need 12+ years experience candidates Your future duties and responsibilities Data Integration Platform Design and Development: • Design, build and implement a framework-based API data ingestion architecture with a low-code/no-code interface for data ingestion and processing using reusable plug-and-play components. • Develop frameworks to consume API components such as JSON payloads, CSVs, etc. • Abstract data to build canonical models and data pipelines to maintain them. • Integrate and process private data securely across multiple AWS accounts with compliance to all security protocols, including PgP encryption and encryption at rest. • Implement data transformations and curate ingested data to ensure high-quality and usable datasets. Integration and Ingestion: • Utilize Databricks and Informatica as unified data integration platforms. • Leverage Kafka (or similar messaging queue) as an enterprise integration tool to ingest and integrate near real time and large volumes of diverse data from multiple sources. • Build frameworks around APIs to bring in data from various sources efficiently. Security and Compliance: • Ensure secure handling of Personally Identifiable Information (PII) data in AWS cloud environments. • Understand and implement secure zones and mechanisms for PII data handling. • Manage data securely across different storage solutions like RedShift and other data warehouses. Multi-Cloud Expertise: • Demonstrate an understanding of different cloud service models - PaaS, SaaS, IaaS, etc. across AWS, Azure, and GCP. • Develop solutions that are compatible with multi-cloud environments, ensuring seamless integration and operation. Continuous Development and Deployment: • Implement continuous development, deployment, testing, integration, and monitoring practices. Use tools like Airflow for workflow automation and scheduling. Required qualifications to be successful in this role Technical Skills: • Proficiency in Python and Spark for data processing and manipulation. • Hands-on experience with Databricks for data analytics and pipeline creation. • Experience with Kafka or similar messaging queues for data ingestion and integration. • Strong SQL skills for database querying and manipulation. • Familiarity with Airflow for workflow management. Cloud Expertise: • Advanced level understanding of the different cloud service models - PAAS, SAAS, IAAS etc. across AWS, Azure and GCP • In-depth knowledge of AWS, including security, data handling, and storage solutions like RedShift and S3 • Understanding of multi-cloud architectures and best practices.

#w2jobs #usajobs #w2requirements #opentowork #lookingfornewopportunities #lookingforjobs #lookingforjob #lookingforjobchange #lookingforwork #lookingfornewjob #recruitment2024 Role: Data Engineer Location: DEARBORN,MI - Only locals. Type: W2 Experience: 7+ Position Description: JOB DESCRIPTION : Deliver, and support custom data products, as well as enhance/expand capabilities. They will work on analyzing and manipulating large datasets supporting public charging locations. The focus will be understanding available data, working with business partners to collect requirements, ensure compliance with Data Governance and OGC use case approvals, creating data products, productionize delivery, profiling, monitoring and ongoing support. They will expand their business knowledge, cross functional collaboration, business intelligence acumen, and technical experience.   Job Description: • Develop EL/ELT/ETL pipelines by using Python/Pyspark to make data available in BigQuery analytical data store from disparate batch, streaming data sources for the Charging / Energy Analytics Product Line. • Orchestrate workflows by using Astronomer (Airflow) that execute ETL data pipelines in a scheduled manner. • Work with Cloud data sources (GCP) understand the data model, business rules behind the data and build data pipelines (with GCP) for one or more business domains. • Build cloud-native services and APIs to support and expose data-driven solutions. • Partner closely with our data scientists to ensure the right data is made available in a timely manner to deliver compelling and insightful solutions. • Design, build and launch shared data services to be leveraged by the internal and external partner developer community. • Building out scalable data pipelines and choosing the right tools for the right job. Manage, optimize and Monitor data pipelines. • Provide extensive technical, strategic advice and guidance to key stakeholders around data transformation efforts. Understand how data is useful to the enterprise. Skills Required: Comfortable with a broad array of relational and non-relational databases. Proven track record of building applications in a data-focused role (Cloud and Traditional Data Warehouse) BigQuery, Astronomer, Python, airflow, DataPro c Skills Preferred: terraform, GCP cloud services, pub sub, Vertex AI, ML Flow Experience Required: • 7+ years of experience with SQL and Python • 2+ years of experience with GCP or AWS cloud services; Strong candidates with 5+ years in a traditional data warehouse environment (ETL pipelines) will be considered • 3+ years of experience building out data pipelines from scratch in a highly distributed and fault-tolerant manner. Regards,  Nagalakshmi vnagalakshmi@mylastech.com

Hi Everyone, We have job opportunity for Senior Data Engineer with one of our clients. Kindly let me know if you are interested or someone who might be interested, please call me or send an updated resume. I can be reached @703-665 5599 x 811 (or) Email: alekya.boda@talteam.com Need 12+ years experience candidates Your future duties and responsibilities Data Integration Platform Design and Development: • Design, build and implement a framework-based API data ingestion architecture with a low-code/no-code interface for data ingestion and processing using reusable plug-and-play components. • Develop frameworks to consume API components such as JSON payloads, CSVs, etc. • Abstract data to build canonical models and data pipelines to maintain them. • Integrate and process private data securely across multiple AWS accounts with compliance to all security protocols, including PgP encryption and encryption at rest. • Implement data transformations and curate ingested data to ensure high-quality and usable datasets. Integration and Ingestion: • Utilize Databricks and Informatica as unified data integration platforms. • Leverage Kafka (or similar messaging queue) as an enterprise integration tool to ingest and integrate near real time and large volumes of diverse data from multiple sources. • Build frameworks around APIs to bring in data from various sources efficiently. Security and Compliance: • Ensure secure handling of Personally Identifiable Information (PII) data in AWS cloud environments. • Understand and implement secure zones and mechanisms for PII data handling. • Manage data securely across different storage solutions like RedShift and other data warehouses. Multi-Cloud Expertise: • Demonstrate an understanding of different cloud service models - PaaS, SaaS, IaaS, etc. across AWS, Azure, and GCP. • Develop solutions that are compatible with multi-cloud environments, ensuring seamless integration and operation. Continuous Development and Deployment: • Implement continuous development, deployment, testing, integration, and monitoring practices. Use tools like Airflow for workflow automation and scheduling. Required qualifications to be successful in this role Technical Skills: • Proficiency in Python and Spark for data processing and manipulation. • Hands-on experience with Databricks for data analytics and pipeline creation. • Experience with Kafka or similar messaging queues for data ingestion and integration. • Strong SQL skills for database querying and manipulation. • Familiarity with Airflow for workflow management. Cloud Expertise: • Advanced level understanding of the different cloud service models - PAAS, SAAS, IAAS etc. across AWS, Azure and GCP • In-depth knowledge of AWS, including security, data handling, and storage solutions like RedShift and S3 • Understanding of multi-cloud architectures and best practices.

Hello Everyone, Greetings of the day! We are #urgenthiring for the below position. Role: Data Architect Remote Contract #C2C #W2 #uscitizens #greencard #independentcontractors Please reach out to me at email(shauryag2639@gmail.com or shaurya.garg@xchangesoft.net) Job Description • This position is a blend of a senior architect and engineer - Data Migration of onprem relational database into cloud data lakehouse • 8+ years on Coding (Python, Java, Scala, or other programming languages), Data warehousing, Database systems (relational and NoSQL),Data analysis, Cloud computing (Azure),Big Data (Hadoop, Hbase), Pyspark, Azure Deltalake, Databricks, DBT, Healthcare domain experience  • Azure Data Factory, Databricks, SQL, Data Architecture, Data Modeling  • Data Migration of onprem relational database into cloud data lakehouse Skills: • Programming Languages: Familiarity with languages like Python or Java for data analysis and application development. • Data Modeling: Proficiency in creating logical and physical data models to represent business requirements and system architecture. • Data Warehousing: Understanding of data warehousing concepts, including data storage, retrieval, and optimization. • Data Security: Knowledge of data security best practices, encryption, and access controls. • ETL (Extract-Transform-Load): Expertise in ETL processes and tools like DBT (Data Build Tool) [DBT Core] and DBT framework/packages • DBT framework/packages - package: dbt-labs/dbt_utils - package: calogica/dbt_date - package: dbt-labs/spark_utils - package: yu-iskw/dbt_unittest - package: mjirv/dbt_datamocktool - package: Datavault-UK/automate_dv • Database Management Systems (DBMS): Proficiency in relational databases (e.g., Microsoft SQL Server) and NoSQL databases. • Cloud Computing: Understanding of cloud platforms (e.g., Azure, AWS, GCP) and their data services. • Delta Lake: Familiarity with Delta Lake, an open-table format that combines data lake flexibility with ACID transactions. • Medallion Architecture: Knowledge of the medallion architecture, which organizes data layers (Bronze, Silver, Gold) in a lakehouse. • Data Vault: Understanding of the Data Vault methodology for scalable and flexible data warehousing. • Azure Data Factory (ADF): Proficiency in using ADF for orchestrating data workflows, data movement, and transformation. Healthcare domain knowledge Saif Shekh Madhuri Chaudhari Jeet Kumar Akanksha P Sachin Tiwari Sunanda Pandey Ashis Kumar Singh Nitesh K. Laxmi Narayan Shivam Rajput Pooja Kumari Manisha Pal Sourabh Singh Chauhan

#w2 #w2jobs #w2requirements #w2contract #w2only #w2hiring #w2position #w2roles #w2job Tittle: Data Engineer Location: DEARBORN,MI – Hybri Work- Only locals.   Position Description: JOB DESCRIPTION The Ford Public Charging Data team is seeking a Data Engineer to create, deliver, and support custom data products, as well as enhance/expand capabilities. They will work on analyzing and manipulating large datasets supporting public charging locations. The focus will be understanding available data, working with business partners to collect requirements, ensure compliance with Data Governance and OGC use case approvals, creating data products, productionize delivery, profiling, monitoring and ongoing support. They will expand their business knowledge, cross functional collaboration, business intelligence acumen, and technical experience.   Job Description: • Develop EL/ELT/ETL pipelines by using Python/Pyspark to make data available in BigQuery analytical data store from disparate batch, streaming data sources for the Charging / Energy Analytics Product Line. • Orchestrate workflows by using Astronomer (Airflow) that execute ETL data pipelines in a scheduled manner. • Work with Cloud data sources (GCP) understand the data model, business rules behind the data and build data pipelines (with GCP) for one or more business domains. • Build cloud-native services and APIs to support and expose data-driven solutions. • Partner closely with our data scientists to ensure the right data is made available in a timely manner to deliver compelling and insightful solutions. • Design, build and launch shared data services to be leveraged by the internal and external partner developer community. • Building out scalable data pipelines and choosing the right tools for the right job. Manage, optimize and Monitor data pipelines. • Provide extensive technical, strategic advice and guidance to key stakeholders around data transformation efforts. Understand how data is useful to the enterprise. Skills Required: Comfortable with a broad array of relational and non-relational databases. Proven track record of building applications in a data-focused role (Cloud and Traditional Data Warehouse) BigQuery, Astronomer, Python, airflow, DataPro c Skills Preferred: terraform, GCP cloud services, pub sub, Vertex AI, ML Flow Experience Required: • 7+ years of experience with SQL and Python • 2+ years of experience with GCP or AWS cloud services; Strong candidates with 5+ years in a traditional data warehouse environment (ETL pipelines) will be considered • 3+ years of experience building out data pipelines from scratch in a highly distributed and fault-tolerant manner.     Best Regards. V.Narendra