Job Title: Senior Data Warehouse Engineer

Job Location: Noida

Job Summary The Senior Data Warehouse Engineer is responsible for designing, developing, implementing, optimizing, and maintaining enterprise-level data warehouse and data engineering solutions. This role will provide technical leadership in the architecture and development of scalable data platforms, ETL/ELT pipelines, data models, database objects, data integrations, and analytics-ready data structures.

The Senior Data Warehouse Engineer will work across traditional and modern cloud data platforms, including Oracle, MongoDB, Snowflake, Databricks, and cloud-native data services. The role will be responsible for building highly scalable, reliable, secure, and high-performing data solutions that support enterprise reporting, analytics, business intelligence, and downstream data applications.

Key Responsibilities

- Design, develop, and maintain enterprise-scale data warehouse and data platform solutions supporting reporting, analytics, business intelligence, and downstream applications.
- Design and implement scalable ETL/ELT pipelines and data integration solutions using Python, SQL/PLSQL, MongoDB, Snowflake, Databricks, and enterprise ETL technologies based on business and technical requirements.
- Develop and maintain enterprise data models, including dimensional models, fact and dimension tables, staging and integration layers, and analytical data structures.
- Implement CDC, SCD Type 1/Type 2, incremental processing, historical data management, data validation, and reconciliation processes.
- Build and optimize cloud-based data solutions using AWS, Azure, or GCP, including applicable storage, compute, integration, and data processing services.
- Implement data quality, monitoring, logging, error handling, auditing, and operational processes to ensure data accuracy, reliability, and availability.
- Troubleshoot and resolve complex data, ETL/ELT, database, performance, and production issues, including root-cause analysis and permanent corrective actions.
- Apply database and data platform performance optimization techniques, including query tuning, execution-plan analysis, partitioning, clustering, indexing where applicable, and workload optimization.
- Develop and maintain technical documentation, including data models, architecture diagrams, source-to-target mappings, technical specifications, and operational procedures.
- Participate in technical design reviews, code reviews, CI/CD, and deployment activities across Development, QA, UAT, and Production environments.
- Collaborate with Data Architects, Product, QA, Business Analysts, Data Analytics, and other technology teams to deliver reliable and scalable data solutions.




- Provide technical leadership and mentoring to junior and mid-level engineers and provide guidance to onshore and offshore development teams.
- Ensure data solutions adhere to enterprise security, data governance, privacy, compliance, and regulatory requirements, including applicable PBM v2.2 and URAC standards.

Qualifications

Education

- Bachelors degree in Computer Science, Information Technology, Engineering, or a related field.

Professional Experience

- Minimum 7 years of experience in Data Warehousing, Data Engineering, Database Development, or related disciplines, including 5+ years designing and developing enterprise data warehouse solutions.
- Minimum 5 years of hands-on experience with SQL/PLSQL, preferably in Oracle environments, including database development and performance optimization.
- Minimum 4 years of experience developing ETL/ELT solutions using Talend, Informatica, SSIS, or equivalent technologies.
- Minimum 3 years of experience with Python and cloud-based data platforms such as Snowflake, Databricks, Redshift, AWS, Azure, or GCP.
- Experience working with MongoDB and other relational or NoSQL databases for data integration and engineering solutions.
- Demonstrated experience working with high-volume data, complex data transformations, production-critical data pipelines, and technical mentoring.

Technical Skills

- Data Warehousing & Architecture: Strong experience designing and implementing enterprise data warehouse, data platform, and lakehouse solutions.
- Database & SQL: Advanced expertise in Oracle SQL/PLSQL, MongoDB, Snowflake SQL and other database technologies.
- Data Modeling: Solid knowledge of dimensional modeling, including fact and dimension tables, star/snowflake schemas, surrogate keys, SCD, and data warehouse design patterns.
- ETL/ELT & Integration: Hands-on experience with ETL/ELT development, CDC, incremental processing, data transformations, source-to-target mapping, and data integration using Talend, Informatica, SSIS, or equivalent.
- Cloud Data Platforms: Experience with Snowflake, Databricks, and cloud platforms such as AWS, Azure, or GCP.
- Big Data & Data Processing: Experience with Databricks, Apache Spark/PySpark, Delta Lake, or comparable distributed data processing technologies.
- Performance & Scalability: Strong experience with SQL/query optimization, execution plans, partitioning, clustering, indexing,



workload optimization, and large-volume data processing.
- Programming & Automation: Proficiency in Python for data engineering, automation, data processing, and integration.
- Data Quality & Governance: Experience implementing data quality, validation, reconciliation, monitoring, auditing, data lineage, security, and governance practices.
- DevOps & Engineering Practices: Experience with Git, CI/CD, automated deployments, production support, and environment management across Development, QA, UAT, and Production.

Preferred Qualifications

- Experience working in healthcare, pharmacy, healthcare benefits, or PBM data environments.
- Experience with PBM data, Medical claims, eligibility, formulary, pharmacy, provider, member, benefit, or healthcare-related datasets.
- Experience with URAC, HIPAA, or other healthcare regulatory and compliance requirements.
- Experience modernizing legacy enterprise data warehouses and migrating workloads from Oracle or other legacy platforms to Snowflake, Databricks, or cloud-native data platforms.
- Experience designing and implementing cloud data warehouse and lakehouse architectures.
- Experience with Spark, PySpark, Delta Lake, or other distributed data processing technologies.
- Experience implementing data catalog, metadata management, data lineage, and enterprise data governance solutions.
- Experience with Agile/Scrum development methodologies.
- Experience with Shell scripting, PowerShell, or other automation technologies.

Additional Requirements

- Ability to manage multiple priorities and deliver complex technical initiatives in a fast-paced enterprise environment.
- Strong written and verbal communication skills.
- Strong ownership, analytical, troubleshooting, and problem-solving abilities.
- Ability to work independently while collaborating effectively with cross-functional teams.
- Ability to participate in production support activities and occasional after-hours support for critical systems, as required.
- Ability to pass a background investigation in accordance with company policy.
- Ability to comply with organizational security, privacy, data governance, and regulatory requirements.

Physical & Mental Requirements

Physical Activities

- Primarily office-based or remote computer work.
- Extended periods of sitting and working at a computer may be required.
- Some travel may be required.

Mental Activities

- Requires sustained analytical thinking, problem-solving, technical decision-making, and attention to detail.
- Requires the ability to analyze complex data architectures, troubleshoot production issues, manage multiple priorities, and communicate technical information effectively.

📌 Urgently Required | Sr. Data Warehouse Engineer | WFO Only (Noida)
🏢 Rxadvance Pbm
📍 Noida