Primary Responsibilities

- Design, build, and operate scalable ETL/ELT pipelines for structured and semi-structured data across internal and external sources

- Develop cloud-native data solutions on up-to-date data platforms (e.g., Databricks lakehouse, Snowflake)

- Apply data modeling, transformations, and enrichment to produce trusted, analytics-ready datasets

- Ensure data quality, reliability, and auditability through validation, reconciliation, and monitoring

- Implement and follow enterprise data governance, security, and compliance standards

- Optimize data workloads for performance, cost efficiency, and operational reliability

- Support modernization efforts, including migration of legacy ETL pipelines to cloud-native architectures

- Partner with product, analytics, and business stakeholders to translate requirements into production-grade data solutions

- Enable downstream analytics, reporting, and AI/ML workloads through well-designed data assets

- Apply software engineering best practices, including CI/CD, version control, testing, and code reviews

- Contribute to architectural discussions and mentor junior engineers

- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI

- Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives. The Company may adopt,



vary or rescind these policies and directives in its absolute discretion and without any limitation on its ability to do so

Required Qualifications

- Bachelor's degree in Computer Science, Engineering related field

- 5+ years of experience as a Data Engineer or in data platform / analytics engineering roles

- 3+ years of experience with SQL, data modeling, and data transformations

- 3+ years of hands-on experience with Databricks and/or Snowflake and large-scale data processing

- 3+ years of experience building ETL/ELT pipelines, data warehouses, and analytical data stores

- 3+ years of experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD)

Preferred Qualifications

- Experience building enterprise-scale data platforms

- Experience with real-time/streaming frameworks (Structured Streaming)

- Exposure to GenAI tools (e.g., GitHub Copilot) for engineering productivity

- Solid understanding of secure coding practices and vulnerability remediation

- Proven ability to work in distributed, cross-functional global teams

- Proven ability to analyze logs, troubleshoot production issues, and optimize performance

- Proven solid skills in performance tuning and debugging large-scale pipelines

- Demonstrated capability to design and deploy AI-powered solutions responsibly

📌 Data Engineer - Pyspark, Databricks, Snowflake, Azure Cloud (Hyderabad)
🏢 Optum
📍 Hyderabad