Source description
About the role
JOB SUMMARY
We are seeking an experienced Data Engineer with strong hands-on Databricks expertise to support the design, development, and optimization of enterprise data solutions. The successful candidate will have deep experience building and maintaining ELT pipelines using native Databricks orchestration, working with large-scale data platforms, and applying modern data architecture principles.
JOB RESPONSIBILITIES
Design, develop, and maintain ELT pipelines using Databricks and related technologies.
Build and optimize large-scale data processing workflows using PySpark and SQL.
Orchestrate multi-stage data pipelines using Databricks Workflows and Jobs, and develop Delta Live Tables (DLT) pipelines with built-in data quality enforcement.
Develop and manage data models to support analytics, reporting, and business intelligence requirements.
Implement and support data Lakehouse architectures and data warehousing solutions.
Collaborate with data analysts, architects, and business stakeholders to understand and deliver on data requirements.
Ensure data quality, integrity, and governance across all data platforms.
Monitor and troubleshoot data workflows, pipeline performance, and platform issues.
Contribute to continuous improvement of data engineering standards and practices.
REQUIRED TECHNICAL SKILLSET
Strong hands-on experience with Databricks (Delta Lake, Databricks Workflows, Unity Catalog)
Strong hands-on experience with Databricks-native orchestration (Databricks Workflows, Jobs) as the primary mechanism for multi-stage pipeline orchestration and scheduling
Experience with Delta Live Tables (DLT) for pipeline development and expectation-based data quality enforcement
Proven experience building and supporting ELT pipelines at scale
Strong proficiency in PySpark and SQL
Experience with data modeling techniques and best practices
Good understanding of data Lakehouse architecture and data warehousing concepts
Experience with version control tools (e.g., Git)
Familiarity with cloud platforms (Azure preferred; AWS or GCP considered)
PREFERRED EXPERIENCE
Experience using Azure Data Factory for data ingestion from source systems, with Databricks Workflows/Jobs as the primary orchestration layer for transformation logic
Experience with Apache Airflow
Exposure to data governance frameworks and tools (e.g., Unity Catalog, Microsoft Purview)
Experience in enterprise consulting or regulated industry environments
Experience working with globally distributed teams across different time zones
CERTIFICATIONS PREFERRED
Databricks Certified Associate Developer for Apache Spark
Databricks Certified Data Engineer Associate or Professional
Microsoft Certified: Azure Data Engineer Associate (DP-203) or equivalent
Additional data or cloud certifications are a plus
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