Data Engineer

Data Ideology•Pittsburgh, PA

1d•Remote

About The Position

At DI, we provide Data & Analytics expertise to drive measurable business outcomes, often solving complex business problems for our clients. Our data analytics advisory services enable our customers to transform data into insights by driving a culture of empowerment and ownership of results. Our team consists of highly motivated individuals passionate about learning, understanding, collaborating, and intellectually curious. For more information about Data Ideology, visit www.dataideology.com We are seeking a hands-on Data Engineer to join our Quality Engineering team. This role is focused on building, maintaining, and optimizing production ETL pipelines and SQL-based data transformations. The ideal candidate has deep, practical ETL experience, strong SQL skills, and can work productively in existing Informatica and Snowflake environments with minimal ramp-up. This is a delivery-focused role for someone who enjoys working directly in pipelines, troubleshooting issues, and supporting data workflows in production

Requirements

5+ years of hands-on experience building and supporting ETL pipelines in production
Strong SQL skills, including complex joins, subqueries, aggregations, and performance tuning
Hands-on experience with Informatica PowerCenter and/or Informatica IICS
Experience working with cloud data warehouses, including Snowflake
Ability to independently troubleshoot ETL failures, data issues, and query performance problems
Experience working within SDLC frameworks and version control systems
Strong communication skills and ability to explain technical work clearly

Nice To Haves

Azure Data Factory (ADF)
Healthcare data experience
Experience supporting migrations from legacy data platforms

Responsibilities

Develop, maintain, and enhance production ETL pipelines using Informatica (PowerCenter and/or IICS)
Write, optimize, and troubleshoot complex SQL used for transformations, validations, and analytics
Support and enhance data pipelines loading into Snowflake
Debug failed ETL jobs, data discrepancies, and performance issues across ETL and warehouse layers
Collaborate with business and technical stakeholders to understand data requirements and translate them into working solutions
Support data warehouse environments across cloud and hybrid architectures
Maintain technical documentation, mappings, and workflow logic
Participate in SDLC processes including deployments, testing, and version control