Data Engineering Consultant - ADB, ADF, Azure, Spark and SQL

Optum; Bengaluru; On-site; INR 2,500,000 - 6,000,000; Full time

Job summary

Optum Bengaluru is seeking a Senior Data Engineer to design and build scalable data pipelines, lead data architecture for warehousing and big data solutions, and optimize performance across data systems. You will ensure data quality, governance, and compliance while collaborating with data scientists, analysts, and business teams to enable analytics and ML initiatives.

Mentorship and automation of deployment processes are expected.

Qualifications

• 7+ years of experience with Spark/Scala and big data tooling.
• Hands-on with Spark, Hadoop or similar frameworks.
• Strong Python/SQL coding and data pipeline development.
• Experience in Azure Databricks, Data Factory and Airflow.
• Knowledge of data warehousing concepts and modeling.

Responsibilities

• Design and build scalable data pipelines (ETL/ELT) for large-scale data.
• Lead data architecture for warehousing and big data solutions.
• Optimize database performance and data workflows.
• Ensure data quality, governance and compliance.
• Collaborate with data scientists, analysts and business teams.

Skills

Spark/Scala

Azure Databricks

Azure Data Factory

Airflow

Kafka

Python/SQL

Cloud Azure/GCP

Docker/Kubernetes

Data Modeling/Warehousing

Distributed Systems

Security & Compliance (GDPR/HIPAA)

Education

Bachelor's degree or equivalent

Tools

Snowflake

Tableau/Power BI

Job description

Responsibilities

• Design and Build Data Infrastructure: Develop and maintain scalable data pipelines (ETL/ELT) for large-scale data processing
• Data Architecture: Lead architectural decisions for data warehousing and big data solutions
• Optimize Performance: Improve database performance, query efficiency, and data workflows
• Data Quality and Governance: Implement frameworks for data validation, monitoring, and compliance
• Collaboration: Work with data scientists, analysts, and business teams to enable analytics and machine learning
• Mentorship: Guide junior engineers and promote best practices in data engineering
• Automation and Deployment: Create automated testing and deployment processes for data systems
• Troubleshooting: Resolve complex data issues and ensure system reliability
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications

• Undergraduate degree or equivalent experience
• 7+ years of experience in Spark/Scala, Azure Databricks, Azure Data Factory, Airflow and Kafka. Proficient in coding, testing, implementing, debugging, and documenting the complex Spark Jobs
• Programming: Solid in Azure Databricks, Python/Scala, SQL experience
• ETL Tools and Big Data: Hands-on experience with Spark, Hadoop, or similar frameworks
• Cloud Platforms: Azure, (or GCP) experience
• Containerization and Orchestration: Docker, Kubernetes
• Data Modeling and Warehousing: Expertise in relational and NoSQL databases
• Distributed Systems: Knowledge of data partitioning and parallel processing
• Data Security and Compliance: Familiarity with GDPR, HIPAA, or similar standards

Preferred Qualifications

• Experience with Snowflake
• Streaming Technologies: Kafka or similar message queuing systems
• AI and Machine Learning Deployment: implementing AI solutions (RAG development, Agents creation), Exposure to ML model integration
• CI/CD for Data: Jenkins or other DevOps tools for data workflows
• BI Tools: Tableau, Power BI for reporting