Data Engineer – Databricks & dbt

Job Title: Data Engineer – Databricks & dbt
Experience: 5+Years

Team: Data Engineering Hub
Platform: OneData / Databricks

Job Summary

We are looking for hands-on Data Engineers to support the development and modernization of data assets on the OneData platform built on Databricks.

The ideal candidate will have strong experience in Databricks, Delta Lake, Apache Spark/PySpark, SQL, and dbt. The role involves building scalable and reusable data pipelines, developing data models across Medallion architecture layers, and implementing engineering best practices for testing, documentation, governance, and deployment.

Candidates should be comfortable working independently, delivering production-quality data solutions, and collaborating with data product teams, solution architects, and engineering leads.

Key Responsibilities

• Design, develop, and optimize data transformations and pipelines using Databricks and dbt.
• Build and maintain data models across Bronze, Silver, and Gold layers of the Medallion architecture.
• Develop scalable and reusable data engineering patterns and frameworks.
• Implement automated data testing, documentation, and deployment practices.
• Optimize SQL queries, data transformations, and Databricks workloads for performance and cost efficiency.
• Apply dimensional data modeling principles to create reliable, high-quality data assets.
• Manage data workflows, dependencies, and lineage across pipelines.
• Collaborate with data product teams, solution architects, and engineering leads to deliver business-ready data solutions.
• Follow established engineering standards, data modeling guidelines, and data quality practices.
• Contribute reusable components and best practices that can be adopted across multiple delivery teams.

Required Technical Skills

Databricks

• Strong hands-on experience with Databricks, Delta Lake, Apache Spark/PySpark, and SQL.
• Experience with Unity Catalog and Databricks Workflows/Jobs.
• Understanding of Medallion architecture and data modeling principles.
• Ability to troubleshoot and optimize data processing workloads.

dbt

• Hands-on experience with dbt Core and/or dbt Cloud.
• Experience developing and managing models, sources, seeds, and snapshots.
• Knowledge of table, view, incremental, and ephemeral materializations.
• Experience with macros and Jinja templating.
• Proficiency in data testing, documentation, and data quality validation.
• Understanding of DAGs, data lineage, package management, and reusable dbt frameworks.

Data Engineering and Development Practices

• Strong SQL skills and experience with dimensional data modeling.
• Proficiency in Python and/or PySpark for data processing and automation.
• Experience with Git-based development and source control.
• Understanding of CI/CD, automated testing, and deployment practices.
• Ability to develop maintainable, scalable, and production-ready data solutions.

Nice-to-Have Skills

• Knowledge of AWS fundamentals, particularly S3 and cloud storage integration.
• Experience in Databricks performance tuning and cost optimization.
• Experience supporting enterprise-scale data platforms.
• Familiarity with reusable data engineering frameworks and development standards.
• Understanding of data governance, access controls, and enterprise data quality requirements.

Ideal Candidate Profile

We are looking for a practical, delivery-focused Data Engineer who can independently develop and maintain production-quality Databricks and dbt solutions. The ideal candidate will be comfortable working within established standards, solving technical problems, and creating reusable engineering patterns that support multiple teams.

How to Apply

Interested candidates can share their updated resume at hr@spasnik.com or reach out via direct message.

Pay: ₹1,500,000.00 - ₹2,500,000.00 per year

Work Location: Hybrid remote in Hyderabad, Telangana