itD is seeking a
Data Engineer to build and maintain scalable data infrastructure that powers company AI product analytics and topline metrics across product surfaces. The ideal candidate will bring strong experience in large-scale data engineering, SQL, Python, data quality, product logging, dashboards, and analytics, with a track record of delivering reliable data pipelines and solutions that support AI-driven products.
Location: Remote
Schedule: 40 hours per week, 5 days per week; no overtime
Duration: 9 Months, with possibility of extension only if the associated leave is extended
Pay Rate: Market Rate, depending on experience.
We provide comprehensive medical benefits, a 401k plan, paid holidays, and more.
Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.
Responsibilities- Design, build, and maintain scalable data pipelines and ETL processes supporting Company AI product analytics and topline metrics.
- Develop and validate product logging, data quality, and monitoring frameworks to ensure reliable and accurate data.
- Build dashboards and analytics reporting solutions that support product tracking, business insights, and decision-making.
- Collaborate with data scientists, analysts, engineers, and cross-functional partners to deliver high-quality data solutions.
- Leverage AI-native tools and workflows to accelerate data engineering development and improve team productivity.
- Troubleshoot and resolve data pipeline, quality, and infrastructure issues while maintaining reliable data operations.
- Document data workflows, processes, and best practices to support knowledge sharing and operational excellence.
Internal Responsibilities- Attend regular internal practice community meetings.
- Collaborate with your itD practice team on industry thought leadership.
- Complete client case studies and learning material (blogs, media material).
- Build out material to contribute to the Digital Transformation practice.
- Attend internal itD networking events (in person and virtual).
- Work with leadership on career fast-track opportunities.
Required Qualifications and Skills- 7+ years of overall professional experience preferred; candidates with less experience may be considered based on strong technical and interpersonal skills.
- Proven experience in data engineering, including building and maintaining ETL/data pipelines.
- Strong experience with SQL and Python for large-scale data engineering.
- Experience building and validating product logging and data quality frameworks.
- Experience developing dashboards and analytics reporting solutions.
- Experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery.
- Experience with at least one major cloud platform, such as AWS, GCP, or Azure.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
- Strong problem-solving, communication, collaboration, and attention-to-detail skills.
Preferred Qualifications and Skills- Prior Meta experience.
- Familiarity with AI-native analytics and development tools.
- Experience supporting AI, GenAI, or machine learning-focused products and data ecosystems.
- Experience working with highly scalable data infrastructure supporting large consumer products.
EducationBachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience required.
Additional InfoDynamic environment in a culture of respect, empowerment and recognition for a job well done, apply today!
