Senior Data Engineer

We are seeking a Senior Data Engineer with expertise in Graph Data technologies to join our data engineering team and contribute to the development of scalable, high-performance data pipelines and advanced data models that power next-generation applications and analytics. This role combines core data engineering skills with specialized knowledge in graph data structures, graph databases, and relationship-centric data modeling, enabling the organization to leverage connected data for deep insights, pattern detection, and advanced analytics use cases. The ideal candidate will have a strong background in data architecture, big data processing, and Graph technologies and will work closely with data scientists, analysts, architects, and business stakeholders to design and deliver graph-based data engineering solutions.

Roles & Responsibilities:

• Design, build, and maintain robust data pipelines using Databricks (Spark, Delta Lake, PySpark) for complex graph data processing workflows.
• Own the implementation of graph-based data models, capturing complex relationships and hierarchies across domains.
• Build and optimize Graph Databases such as Stardog, Neo4j, Marklogic or similar to support query performance, scalability, and reliability.
• Implement graph query logic using SPARQL, Cypher, Gremlin, or GSQL, depending on platform requirements.
• Collaborate with data architects to integrate graph data with existing data lakes, warehouses, and lakehouse architectures.
• Work closely with data scientists and analysts to enable graph analytics, link analysis, recommendation systems, and fraud detection use cases.
• 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.
• 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.

What we expect of you

Must-Have Skills:

• Hands-on experience in Databricks, including PySpark, Delta Lake, and notebook-based development.
• Hands-on experience with graph database platforms such as Stardog, Neo4j, Marklogic etc.
• Strong understanding of graph theory, graph modeling, and traversal algorithms
• Proficiency in workflow orchestration, performance tuning on big data processing
• Strong understanding of AWS services
• Ability to quickly learn, adapt and apply new technologies with strong problem-solving and analytical skills
• Excellent collaboration and communication skills, with experience working with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices.

Good-to-Have Skills:

• Good to have deep expertise in Biotech & Pharma industries
• Experience in writing APIs to make the data available to the consumers
• Experienced with SQL/NOSQL database, vector database for large language models
• Experienced with data modeling and performance tuning for both OLAP and OLTP databases
• Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops

Education and Professional Certifications

• Master s degree and 3 to 4 + years of Computer Science, IT or related field experience
• Bachelor s degree and 5 to 8 + years of Computer Science, IT or related field experience
• AWS Certified Data Engineer preferred
• Databricks Certificate preferred
• Scaled Agile SAFe certification preferred

Soft Skills:

• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.
• Ability to learn quickly, be organized and detail oriented.
• Strong presentation and public speaking skills.