Databricks Data Engineer

CentricaSoft is a modern technology partner focused on Gen AI–driven enterprise data transformation. The company helps organizations unlock the full value of their data through advanced AI/ML solutions, large-scale data modernization, Master Data Management (MDM) solutions, and cloud-native architectures. Its services span business intelligence and analytics, data integration and governance, compliance and risk management, and DevOps operations. By delivering scalable data lake solutions, petabyte-scale processing, and Talent-as-a-Service (TaaS), CentricaSoft supports enterprises in making smarter decisions, improving efficiency, and driving innovation.

We are looking for a Lead Data Engineer to architect scalable data pipelines, drive data strategy, and mentor a team of talented engineers. If you live and breathe Spark, Delta Lake, and modern data architectures, we want you on our team!

What you will be doing:

Architect, build, and optimize scalable enterprise data pipelines and ELT processes using Databricks and Apache Spark.

Lead the design of robust data models, Delta Lake architectures, and scalable data warehouse solutions.

Mentor and guide data engineering pods, establishing best practices for code reviews, testing, and system architecture.

Drive CI/CD implementations, automating the deployment of complex data pipelines and cloud infrastructure.

Partner directly with cross-functional stakeholders to translate complex business and analytics requirements into technical solutions.

Monitor, troubleshoot, and aggressively optimize the performance and compute cost of Databricks clusters and Spark jobs.

What you need to bring to the table:

✅ Mandatory: Active Databricks Certified Data Engineer certification (Associate or Professional level). ✅ 7+ years of dedicated data engineering experience, with a proven track record in a leadership, senior, or architectural role.

✅ Expert-level proficiency in Python and/or Scala, alongside advanced SQL capabilities for deep data manipulation.

✅ Deep hands-on expertise with the Databricks ecosystem (Delta Lake, Unity Catalog, Databricks Workflows).

✅ Strong cloud infrastructure experience operating within AWS, Azure, or GCP environments.

✅ Hands-on experience with orchestration tools (e.g., Airflow), modern API data ingestion mechanisms, and distributed processing.

Ready to take ownership of enterprise-scale data platforms and lead a top-tier technical team?