Data Engineer - MDM; W2

Key Responsibilities:

Design, develop, and deploy scalable and secure data pipelines and cloud-native architectures (data lakes, warehouses, and streaming pipelines) on AWS.

Build and maintain ETL/ELT workflows using AWS Glue, Lambda, and Python to support a variety of data integration needs.

Develop, deploy, and optimize APIs to enable seamless data access for business intelligence, analytics, and operational systems.

Analyze, debug, and resolve data quality issues and pipeline failures to ensure data accuracy and reliability.

Collaborate across teams—including data science, analytics, and software engineering—to design and implement reusable data models.

Ensure efficient, scalable, and secure serverless operations through performance tuning and best practices in AWS environments.

Create and maintain documentation, architecture diagrams, and data flow maps for internal and external use.

Implement and manage data governance, security protocols, compliance standards, and privacy best practices.

Incorporate AI tools, such as ChatGPT, to streamline engineering tasks, documentation, and data exploration.

Lead integration efforts with third-party APIs and data sources to expand the organization’s data capabilities.

Establish and enforce architectural best practices, CI/CD pipelines, and Infrastructure as Code (IaC) in collaboration with Dev Ops teams.

Mentor team members, stay current with AWS innovations, and champion modern data practices across the organization.

Bachelor’s degree in computer science, Information Systems, Analytics, or related field.

5+ years of experience in data architecture, engineering, or similar roles.

3+ years of hands‑on programming experience with Python.

3+ years of experience building and managing ETL/ELT data pipelines.

Strong SQL skills and ability to write performant queries across various data stores.

Proficient with AWS services:
Lambda, Glue, S3, DynamoDB, Athena, Redshift, and Snowflake.

Solid understanding of OLTP, ODS, and dimensional modeling techniques.

Experience designing APIs and integrating with API‑driven data workflows.

Strong knowledge of serverless architecture patterns and best practices.

Excellent problem‑solving, analytical, and communication skills.

Experience in agile development environments with CI/CD workflows.

Ability to collaborate across engineering, data, and business teams.

AWS Certifications (e.g., AWS Solutions Architect).

Experience with modern data stack tools such as dbt, Snowflake, Databricks.

Familiarity with machine learning pipelines and AI‑driven analytics.

Experience with Infrastructure as Code (IaC) tools like Terraform or AWS Cloud Formation.

Background in Dev Ops and automated deployment strategies for data workflows.

Experience integrating with Service Now application.