Data Engineer Data Quality & Analytics

Overview

About the job:

Our Client is building a data platform where product, analytics, and customer-facing decisions rely on accurate, consistent, and timely data.As we scale, ensuring the integrity of data across pipelines, transformations, and downstream systems becomes critical.
Role OverviewYou will work across the data stack to ensure that data flowing through our systems remains reliable, consistent, and aligned with business expectations.This involves working closely with data pipelines, transformations, and analytical layers to identify inconsistencies, investigate anomalies, and improve overall data quality.
ResponsibilitiesWork with data pipelines across ingestion, transformation, and warehouse layersInvestigate discrepancies in metrics, dashboards, and downstream data systemsTrace data issues across multiple stages (source - transformation - output)Collaborate with product and analytics teams to understand data usage and expectationsImprove reliability of data systems through validation, monitoring, and process improvementsContribute to improving how data issues are identified, understood, and resolved
What Were Looking ForExperience working with data pipelines and transformations (e.g., Airflow, Spark/PySpark, DBT, SQL-based workflows)Experience working on cloud platforms (GCP or AWS)Strong SQL and working knowledge of PythonExperience debugging issues in production data systemsFamiliarity with data warehouses (BigQuery, Snowflake, Redshift, etc.)
Strong SignalsExperience working on data that supports product, growth, or business reportingAbility to reason about how data changes impact metrics and downstream use casesExperience working with large datasets and understanding their structure and behaviorComfortable collaborating with both engineering and non-technical stakeholders
What Youll Work OnInvestigating unexpected changes in key metricsUnderstanding inconsistencies across dashboards and data sourcesImproving trust in data used by product and business teamsEnsuring data systems scale reliably as usage grows
Ideal BackgroundsData Engineers working on analytics or product dataAnalytics Engineers working with transformation layers (DBT, SQL models)Engineers who have worked closely with business or product teams on data-driven systems
Why This RoleYoull be working at the intersection of data engineering and product impact, where understanding data correctness is as important as building the systems themselves.

Who can apply:

Only those candidates can apply who:

1. have minimum 4 years of experience
2. are Computer Science Engineering students

Salary:

Competitive salary

Experience:

4 year(s)

Deadline:

2026-10-06 23:59:59