Lead Data Engineer

Job Description

Data Engineering Lead / Manager – Data Lakehouse 

We are looking for an experienced Data Engineering Lead / Manager to provide technical and delivery leadership for a large-scale enterprise Data Lakehouse transformation. 

The successful candidate will lead a team of data engineers and technical specialists, working closely with business stakeholders, architects and platform teams to design and deliver scalable, secure and governed data solutions. 

Key Responsibilities 

Lead the design and delivery of enterprise-scale Data Lakehouse and data engineering solutions. 

Lead and mentor data engineering teams across multiple delivery workstreams. 

Drive the development of batch, streaming and real-time data pipelines. 

Lead data modeling across Silver and Gold layers, including modernization of legacy data models and source-to-target mappings. 

Establish engineering standards covering development, testing, CI/CD, monitoring and operational support. 

Provide technical leadership across data migration, reconciliation, data quality and governance. 

Review solution designs and ensure scalability, performance, security and maintainability. 

Coordinate technical dependencies, risks and issues across engineering, architecture and migration teams. 

Work closely with business stakeholders, architects, SMEs and implementation partners. 

Support planning, estimation and successful end-to-end delivery of the program. 

What We're Looking For 

10+ years' experience in data engineering, data platforms, data warehousing or related areas. 

Strong experience leading technical teams and complex enterprise data programs. 

Hands-on understanding of modern Lakehouse architectures and data engineering patterns. 

Strong experience with Spark/PySpark, SQL, Kafka and Apache Iceberg. 

Experience with Cloudera Data Platform (CDP) or similar enterprise data platforms. 

Strong understanding of data modeling, ETL/ELT, data migration and data quality. 

Experience with CI/CD, automation, monitoring and production-grade data engineering. 

Strong stakeholder-management and technical leadership skills. 

Good to Have 

Experience in one or more of the following would be advantageous: 

Banking or financial services 

Apache NiFi, Flink or Airflow 

Cloudera ecosystem technologies 

Data governance tools such as Atlas, Ranger or Informatica 

Denodo or semantic/analytics layers 

Large-scale data migration or EDW modernization 

Regulatory or governance-driven data environments 

AI and advanced analytics platforms