Data Quality Engineer

Job Description

1. Data Governance & Lineage:
Proven experience enforcing data governance policies, managing data catalog, and mapping end-to-end
Data Lineage
from source to visualization layers.
2. Strong SQL & Data Profiling:
Advanced proficiency in writing complex SQL queries to profile datasets, monitor schema drift, and identify structural anomalies.
3. Python Programming:
Strong scripting skills in Python to build automated validation tests and interact with APIs/governance frameworks.
4. Contemporary Data Stack (MDS):
Hands-on architecture experience with cloud data platforms like
Snowflake
or Databricks.
5. Data Quality Tools:
Practical experience using testing and governance frameworks such as
Great Expectations
,
dbt test
,



or enterprise catalog (e.g., Collibra, Informatica).
6. Data Pipelines & Orchestration:
Solid understanding of ETL/ELT pipelines and orchestration tools (
Apache Airflow
or Prefect) to embed quality checks and compliance controls directly into data workflows.

Preferred / Nice-to-Have:

1. Familiarity with data privacy regulations (e.g., GDPR, CCPA) and data masking techniques.
2. Experience with Big Data processing (Apache Spark/PySpark).
3. Experience with Data Observability platforms.
4. Mandate: Collibra / Alation / Microsoft Purview

📌 Data Quality Manager (Hyderabad)
🏢 Cyient
📍 Hyderabad