Database Administrator

Experience: 3–6 Years
Salary: 4 to 9 LPA

We’re looking for a passionate Data Engineer / Data Test Engineer to join our growing digital engineering team.

In this hybrid role, you’ll design and validate modern data pipelines and warehouse systems that power analytics and business intelligence solutions across enterprises. You’ll work closely with cross-functional teams to ensure data accuracy, scalability, and quality — combining strong engineering skills with a keen eye for testing and automation.

If you enjoy solving complex data challenges, building high-performing ETL workflows, and ensuring data integrity through automation and testing — this role is for you.

• Proven experience (3–6 years) in data engineering, ETL development, or data validation.
• Strong analytical mindset with a focus on data accuracy, performance, and reliability.
• Hands-on experience with ETL/ELT tools (Azure Data Factory, Databricks, dbt, Glue).
• Excellent SQL and Python skills, including experience with PySpark.
• Exposure to cloud data platforms (Azure, AWS) and data warehousing (Snowflake, Databricks).
• Familiarity with data quality testing frameworks such as Great Expectations, dbt test, or PyTest.
• Strong communication skills to collaborate effectively with engineers, QA teams, and analysts.

• Build and optimize end-to-end data pipelines ensuring accuracy and scalability.
• Implement data validation and quality automation within CI/CD workflows using Azure DevOps.
• Conduct data profiling, reconciliation, and lineage validation to ensure clean data ecosystems.
• Collaborate with QA, DevOps, and data teams to ensure observability and governance across environments.
• Work with structured and semi-structured data formats (CSV, Parquet, JSON, XML).
• Leverage GenAI tools (AWS Bedrock, Azure AI) for data testing and automation.

• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• Certification in AWS/Azure Data Engineering, ETL Testing, or Cloud Data Services.
• Exposure to GenAI-assisted testing or data observability platforms (Monte Carlo, Soda, etc.).
• Experience integrating data workflows into CI/CD pipelines and managing version control via GitHub.

• Work in a high-growth digital engineering environment with global exposure.
• Collaborate with cross-functional agile teams solving real business problems.
• Access to continuous learning programs, certifications, and mentorship.
• Opportunity to grow into Data QA Lead / Data Architect roles.
• Flexible hybrid work model – balance collaboration and focus time.
• Be part of a culture that values innovation, ownership, and empathy.

Explore and find out why we are made for each other: Life at OptiSol

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