Senior Data Engineer

Senior Data Engineer

Roles & Responsibilities

• Graph Data Engineering:

  Design, build, and maintain robust data pipelines using

  Databricks

  (

  Spark, Delta Lake, PySpark

  ) for complex graph data processing workflows.

• Graph Database Optimization:

  Own the implementation of graph-based data models, capturing complex relationships and hierarchies. Build and optimize

  Graph Databases

  such as

  Stardog, Neo4j, Marklogic

  , or similar, to support query performance, scalability, and reliability.

• Query Implementation:

  Implement graph query logic using

  SPARQL, Cypher, Gremlin, or GSQL

  , depending on platform requirements.

• Data Integration & Analytics:

  Collaborate with data architects to integrate graph data with existing data lakes and warehouses. Work closely with data scientists and analysts to enable graph analytics, link analysis, and recommendation systems.

• Metadata & Governance:

  Develop metadata-driven pipelines and lineage tracking for graph and relational data processing. Ensure data quality, governance, and security standards are met across all graph data initiatives.

• Mentorship & Innovation:

  Mentor junior engineers and contribute to data engineering best practices, especially around graph-centric patterns and technologies. Stay up-to-date with the latest developments in graph technology, graph ML, and network analytics.

Qualifications

• A Master's or Bachelor's degree in Computer Science, IT, or a related field with relevant experience.
• Hands-on experience in

  Databricks

  , including

  PySpark

  and

  Delta Lake

  .
• Hands-on experience with graph database platforms such as

  Stardog, Neo4j, or Marklogic

  .
• Strong understanding of

  graph theory, graph modeling

  , and traversal algorithms.
• Proficiency in workflow orchestration and performance tuning on big data processing.
• Strong understanding of

  AWS services

  .
• Experience with software engineering best practices, including version control (

  Git

  ),

  CI/CD

  (Jenkins), and automated unit testing.

• AWS Certified Data Engineer

  ,

  Databricks Certificate

  , or

  Scaled Agile SAFe certification

  is preferred.

Soft Skills

• Problem-Solving:

  Excellent analytical and troubleshooting skills, with the ability to quickly learn, adapt, and apply new technologies.

• Collaboration:

  Excellent collaboration and communication skills, with experience working with

  Scaled Agile Framework (SAFe)

  and

  DevOps

  practices.

• Proactiveness:

  High degree of initiative and self-motivation, with the ability to manage multiple priorities successfully.

• Communication:

  Strong verbal and written communication skills, including presentation and public speaking skills.