Senior Lead Data Engineer - Databricks

10-12 Years

Posted 2 hours ago
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Job Description

Description

We're on the lookout for exceptional individuals to join our team as Senior Lead Data Engineers - Databricks. As part of our team, you'll play a key role in designing and delivering modern, scalable data platforms for clients across multiple industries, leveraging Azure and Databricks technologies.

You will lead the design, development, and optimization of end-to-end data engineering solutions built on modern Lakehouse architectures. Working closely with clients and cross-functional teams, you'll translate business requirements into scalable, high-performance data platforms while mentoring engineers and driving technical excellence.

Requirements

Responsibilities

Lead the design, development, and maintenance of scalable data engineering solutions using Azure and Databricks.
Design and implement modern Lakehouse architectures following industry best practices.
Build and optimize large-scale batch and streaming data pipelines.
Develop ETL/ELT pipelines using Databricks, PySpark, SQL, and Azure Data Factory.
Design, implement, and optimize Delta Lake solutions for reliable and performant data processing.
Collaborate with clients to gather requirements and translate business needs into technical solutions.
Optimize Spark workloads for performance, scalability, and cost efficiency.
Design and maintain enterprise-grade Data Warehouses, Data Lakes, and Lakehouses.
Implement data governance, security, and metadata management using Azure services such as Purview, Key Vault, and Microsoft Entra ID (Azure Active Directory).
Establish CI/CD pipelines and DevOps practices for data engineering workloads.
Mentor and coach junior data engineers while promoting engineering best practices.
Participate in architecture discussions, solution design, and technical leadership initiatives.
Contribute to internal knowledge sharing and continuous improvement.

Requirements
Required

10+ years of professional experience in Data Engineering.
4+ years of hands-on experience with Databricks.
Strong experience developing data pipelines using PySpark and Apache Spark.
Strong experience designing and implementing Lakehouse architectures.
Experience working with Delta Lake and Medallion Architecture.
Strong knowledge of SQL and Python.
Experience with Azure Data Factory.
Experience working with Azure Data Lake Storage Gen2 (ADLS Gen2).
Experience with Azure Synapse Analytics.
Experience with Data Warehousing concepts and dimensional modeling.
Strong understanding of ETL and ELT design patterns.
Experience optimizing Spark jobs, partitioning strategies, joins, caching, and workload performance.
Experience with Git and Azure DevOps CI/CD pipelines.
Experience implementing secure data platforms using Azure Key Vault, Microsoft Entra ID, and Microsoft Purview.
Experience building scalable enterprise data platforms in Azure.
Experience working directly with clients and gathering technical requirements.
Experience mentoring engineers and leading technical initiatives.

Strongly Preferred

Experience with Snowflake.
Experience building real-time streaming solutions using Structured Streaming, Kafka, or Event Hubs.
Experience with Databricks Workflows.
Experience with Delta Live Tables.
Experience with Unity Catalog.
Experience with Databricks SQL.
Experience with MLflow.
Experience with dbt.
Experience with Airflow or other orchestration platforms.
Experience working in Agile environments.