Senior Data Engineering Lead

CommServe Technologies Inc

1d•Remote

About The Position

We are seeking an experienced Senior Data Engineering Lead to drive enterprise data platform architecture, lead data engineering initiatives, and mentor a growing team of engineers. This role combines strategic leadership with deep technical expertise in modern cloud data platforms, particularly the Azure ecosystem and Databricks Lakehouse architecture. The ideal candidate will take ownership of data engineering standards, governance frameworks, and scalable data solutions while ensuring high data quality, security, performance, and regulatory compliance aligned with healthcare industry standards.

Requirements

Strong hands-on experience with: Azure Data Factory Azure Data Lake Storage Azure Databricks Azure Synapse Analytics
Proven experience designing enterprise-scale data pipelines and lakehouse architectures.
Mandatory expertise in Databricks Unity Catalog, including governance implementation, lineage tracking, access control policies, and metadata management.
Strong experience in ETL/ELT development, data warehousing, and dimensional data modeling.
Advanced proficiency in Python, SQL, Spark, JSON, and modern data engineering frameworks.
Experience integrating enterprise systems such as ERP, CRM, and healthcare/SaaS platforms where applicable.
Solid understanding of data governance, security protocols, RBAC, data lineage, and data quality practices.
Experience working in Agile environments with DevOps, CI/CD pipelines, and version control tools (Git, Jenkins, Jira).

Nice To Haves

Experience in healthcare, diagnostics, or regulated data environments.
Experience implementing large-scale cloud data modernization programs.
Exposure to real-time data pipelines, streaming platforms, and API-driven architectures.
Experience with BI/visualization tools such as Power BI, Tableau, or similar platforms.
Strong stakeholder communication and consulting experience.
Experience mentoring distributed or global teams.

Responsibilities

Lead, mentor, and develop a high-performing data engineering team.
Provide technical guidance, architectural oversight, and code reviews.
Establish engineering best practices, standards, and governance frameworks.
Foster collaboration across engineering, analytics, BI, and business teams.
Drive knowledge sharing, technical upskilling, and continuous improvement.
Design, implement, and maintain scalable data pipelines across cloud and hybrid environments.
Architect modern lakehouse /data warehouse solutions using Azure and Databricks.
Develop robust ETL/ELT frameworks ensuring reliability, performance, and scalability.
Lead integration of data from enterprise systems, SaaS platforms, APIs, and on-premises sources.
Define data models optimized for analytics, reporting, and advanced analytics use cases.
Implement enterprise-grade data governance using Databricks Unity Catalog.
Establish data lineage, access controls, metadata management, and security policies.
Ensure compliance with healthcare security and regulatory standards where applicable.
Build data quality monitoring, observability, and reliability frameworks.
Develop long-term data platform strategy aligned with organizational goals.
Drive cloud data modernization and optimization initiatives.
Collaborate with business stakeholders to translate requirements into scalable solutions.
Support BI and analytics teams with governed, high-quality datasets.