Senior Data Engineer – Enterprise AI Analytics Enablement
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Job Location:
New York City, NY - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
Senior Data Engineer Enterprise AI / Analytics Enablement
Location: NYC (Hybrid; 3 4 days onsite)
Start: Immediate / January
Duration: 3 Months
Employment Type: W-2 ONLY
Role Overview
We are seeking a hands-on execution-focused Senior Data Engineer to support a high-visibility enterprise AI initiative for a major public-sector client. This role is data-first not application-first and focuses on ingestion transformation validation and operational readiness of data feeding analytics dashboards and AI systems.
This is a heads-down delivery role The expectation is immediate impact with minimal ramp-up.
- What You Will Do
- Build maintain and troubleshoot ETL / ELT data pipelines
- Clean normalize validate and structure data for:
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- analytics dashboards
- AI / LLM consumption
- UAT and audit-ready workflows
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- Work with structured and semi-structured data (tables logs extracted document data)
- Partner closely with:
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- AI engineers (ensuring data is AI-ready)
- Application engineers (ensuring data is consumable)
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- Support UAT execution including test-data preparation and defect triage
- Ensure traceability and audit readiness from source pipeline output
- Debug data quality and pipeline issues under tight timelines
Required Experience (Non-Negotiable)
- 6 years of hands-on data engineering experience
- Strong SQL (writing debugging optimizing complex queries)
- Proven ownership of production data pipelines
- Experience with one or more modern data platforms such as:
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- Azure Data Factory / Synapse / Databricks
- AWS Glue / Redshift
- Snowflake / BigQuery
- Informatica / Talend
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- Experience supporting analytics or dashboarding layers (Power BI Tableau Looker etc.)
- Comfortable operating in fast-paced consulting environments
- Able to deliver clean outputs with partial or evolving requirements
Strongly Preferred
- Experience preparing data for AI / ML or GenAI workflows
- Experience with OCR-extracted or document-derived data
- Familiarity with Azure environments
- Prior experience on regulated or public-sector projects
- Experience working alongside McKinsey Big-4 or similar consulting teams
What This Role Is NOT
- Not a frontend or UI role
- Not a data science or modeling role
- Not a research or experimentation role
- Not reporting-only or analyst work
This is engineering and execution not theory.
What Success Looks Like
- Data pipelines are stable auditable and trusted
- Dashboards and AI systems receive clean validated inputs
- UAT sessions run smoothly with minimal data surprises
- The team is never blocked waiting on data
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
