Senior Data Engineer Specialist

Title: Data Engineer, Specialist

Location: Remote(Consultant need to work in EST time zone)

Domain: Healthcare

Key Responsibilities/ Accountabilities: Listing of key responsibilities / major activities necessary to fulfill the position's purpose. If possible, please include the percentage of time spent on each key responsibility.

Advanced Data Engineering and Solution Design (40%)

Architect and implement scalable data pipelines to process and integrate structured and unstructured data.

Design end-to-end data solutions, including data lakes, warehouses, and marts, to support analytics and operational systems.

Collaborate with stakeholders to translate business requirements into scalable, high-performing data architectures.

Data Governance and Compliance (30%)

Develop and enforce data governance standards, ensuring consistency, accuracy, and compliance with regulatory frameworks (e.g., GDPR, HIPAA).

Implement data lineage, metadata management, and auditability practices using tools like Apache Atlas or AWS Glue Data Catalog.

Establish and manage data stewardship frameworks to improve data quality and trust across the organization.

Collaboration and Mentorship (20%)

Partner with analytics, AI/ML, and software engineering teams to ensure seamless data integration and usability.

Mentor junior data engineers on best practices in data governance, solution design, and modern engineering techniques.

Performance Optimization and Security (10%)

Optimize system performance by designing and implementing data partitioning, indexing, and compression strategies.

Ensure data security through access controls, encryption, and secure design practices.

Education and Experience

Bachelor's or master's degree in computer science, Engineering, or related field.

10+ years of experience in data engineering, with a strong emphasis on data governance and solution design.

Expertise in developing scalable data architectures for enterprise reporting and AI/ML applications.

Core Competencies

Proficiency in distributed data frameworks like Apache Spark and Flink.

Experience with enterprise data modeling (e.g., Erwin, dbt, SQL Data Modeler) and Integration (e.g. POSTMAN, SOAP-UI) tools

Advanced knowledge of data governance tools and frameworks, such as Apache Atlas or Collibra.

Strong understanding of cloud platforms and data services, including AWS Redshift, Azure Synapse, and Google Cloud Platform BigQuery.

Additional Qualifications:

Excellent analytical and troubleshooting skills with attention to detail.

Strong communication skills to effectively articulate technical concepts to non-technical stakeholders.

Ability to prioritize tasks in a dynamic environment and manage multiple initiatives simultaneously.

Certifications in cloud, database, and programming are a plus.