Data Steward/Analyst – Nearshore

Data Steward / Data Analyst (Contract, Ongoing) Data Quality & Governance

Role Overview Our client, a growing data analytics company serving the retail and manufacturing sector, is seeking a contract Data Steward/Data Analyst to own data quality management on an ongoing basis as ingestion volume and source complexity scale. This is a standing engagement, not a fixed scope project, built to absorb data quality operations so core data engineering and analytics staff can stay focused on platform and model development.

What You’ll Do
Own data quality monitoring across multi source ingestion pipelines (SKU level inventory, pricing, assortment, and distribution feeds from retail and manufacturer clients)
Design and implement data quality checks, including schema validation, null/outlier detection, referential integrity, deduplication logic, and freshness/SLA monitoring, using frameworks such as dbt tests, Great Expectations, or equivalent
Build and maintain master data management (MDM) logic to establish a canonical single source of truth across disparate, overlapping client datasets
Profile incoming datasets to identify drift, schema changes, and anomalies before they propagate downstream
Maintain and extend dbt models (staging, intermediate, mart layers) including testing, documentation, and lineage tracking
Write and optimize complex SQL against large scale, columnar data warehouses
Support and troubleshoot ETL/ELT pipelines, coordinating with data engineering on root cause resolution for pipeline level quality failures
Establish data quality scorecards/dashboards and report metrics and trends to stakeholders
Document data definitions, lineage, and stewardship SOPs to make quality standards auditable and repeatable
Partner cross functionally with data engineering, analytics, and client facing teams to prioritize fixes based on downstream business impact

Required Skills & Experience
3+ years in a data analyst, data steward, data quality engineer, or analytics engineer role
Advanced SQL: window functions, query optimization, and experience working at scale in a columnar/OLAP warehouse (ClickHouse, Snowflake, BigQuery, Redshift, or similar; transferable warehouse experience welcome)
Hands on ETL/ELT pipeline experience, including debugging and data validation at the pipeline level
Production experience with dbt: models, tests, macros, and documentation
Working knowledge of a major cloud platform (AWS preferred; Azure/GCP experience also considered)
Familiarity with data quality/observability tooling (Great Expectations, Monte Carlo, dbt tests, or similar)
Comfort with Python or similar scripting language for data profiling and automation
Understanding of data modeling concepts: dimensional modeling, star/snowflake schema, slowly changing dimensions
Experience with large scale, multi source datasets (millions+ rows, multiple concurrent client feeds)
Retail or B2C industry background strongly preferred; SKU level, pricing, or inventory data experience a major plus
Git/version control proficiency for pipeline and model changes
Strong documentation discipline and ability to work independently on an ongoing cadence

Engagement Type
Ongoing contract (not project based); structured for continuous coverage