Primary (Must Have) Skills
10+ years of experience in Data Engineering, Data Integration, or Data Platform delivery.
Strong hands-on experience with Databricks on AWS.
Expertise in Apache Spark, PySpark, Delta Lake, and Lakehouse architecture.
Experience designing and implementing enterprise-scale data pipelines.
Strong understanding of AWS services such as S3, Glue, Lambda, Redshift, IAM, and CloudWatch.
Hands-on experience with MDM implementations and integrations.
Experience with data quality, data governance, lineage, and master data management processes.
Strong experience integrating enterprise systems using middleware platforms such as MuleSoft, Boomi, Kafka, or API-based integrations.
Experience working with structured, semi-structured, and unstructured datasets.
Strong SQL and Python development skills.
Experience with Agile delivery methodologies and DevOps practices.
Experience leading distributed teams and managing stakeholder communications.

Secondary Skills (Good to Have)
Experience with Snowflake or Microsoft Fabric.
Exposure to AI/ML enablement using Databricks ML or AWS SageMaker.
Experience with Unity Catalog and data governance frameworks.
Knowledge of Data Mesh and Data Product concepts.
Experience with real-time streaming using Kafka or Kinesis.
Experience with Informatica IDMC, Talend, or Azure Data Factory.
Knowledge of Healthcare, life sciences, retail, manufacturing, or financial services domains.
Exposure to GenAI and enterprise AI adoption initiatives.

Role Summary
Client is seeking a seasoned Data Engineering Lead with strong expertise in Databricks on AWS, MDM, and enterprise data integration.
The candidate will lead the design and delivery of modern data platforms that enable trusted, governed, and scalable data consumption across business functions.
This role requires deep experience in cloud-based data engineering, middleware integrations, data governance, and enterprise-scale analytics solutions.
The ideal candidate will work closely with business, architecture, analytics, and engineering teams to drive data modernization initiatives.

Why This Role Matters
This role will be instrumental in enabling the client's enterprise data modernization journey.
The individual will help establish a scalable and governed data foundation that supports advanced analytics, AI/ML initiatives, and business decision-making.
Success in this role will directly improve data quality, consistency, and accessibility across critical business domains.

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Enterprise Data Architect

TechNeptune Consulting Inc.