Data Quality Engineer

About Gradera

Gradera defines a new category of enterprise transformation called Software-Orchestrated Services™ - where software orchestrates human expertise, digital workers, and enterprise systems to deliver governed outcomes at scale. As an AI Native Services firm, we help enterprises redesign how work gets done across operations, product, engineering, customer experience, data, and enterprise workflows to move beyond fragmented AI pilots and disconnected automation toward measurable business outcomes.

Data Quality Engineer

Location: Hyderabad, Telangana

Department: Engineering

Employment Type: Full-Time

Overview

We are seeking a detail-oriented Data Quality Engineer to ensure the integrity, accuracy, and reliability of data powering our digital twin and AI platforms. You will design and implement data quality frameworks, build automated validation pipelines, and establish quality metrics that enable trusted, simulation-ready data products. This role is critical to ensuring that operational decisions and ML models are built on a foundation of high-quality, governed data.

Our core data quality stack includes:

Data Quality Frameworks

Delta Live Tables expectations for declarative quality enforcement

Great Expectations for comprehensive data validation

Databricks data profiling and quality monitoring

Platform & Tools

Databricks SQL and PySpark for quality checks at scale

Unity Catalog for lineage tracking and governance compliance

Python for custom validation logic and anomaly detection

Observability

Quality metrics dashboards and alerting

Data profiling and statistical analysis

Anomaly detection and drift monitoring

Key Responsibilities

Design and implement data quality frameworks using Delta Live Tables expectations and Great Expectations

Build automated data validation pipelines that enforce quality standards at ingestion and transformation stages

Develop data profiling processes to understand data distributions, patterns, and anomalies

Define and track data quality metrics (completeness, accuracy, consistency, timeliness, validity)

Implement anomaly detection mechanisms to identify data drift and quality degradation

Create quality dashboards and alerting systems for proactive issue identification

Collaborate with data engineers to embed quality checks into ETL/ELT pipelines

Partner with data architects to establish data quality standards and governance policies

Investigate and perform root cause analysis for data quality issues

Document data quality rules, thresholds, and remediation procedures

Support data certification processes for simulation-ready and ML-ready datasets

Drive continuous improvement in data quality practices and tooling

Preferred Qualifications

6+ years of experience in data engineering or data quality roles, with 3+ years focused on data quality

Track record of implementing enterprise-scale data quality frameworks

Experience with Lakehouse architectures (Delta Lake, Iceberg)

Familiarity with real-time data quality monitoring for streaming pipelines

Experience working in agile, cross-functional teams

Highly Desirable

Experience with data quality for digital twin or simulation platforms

Familiarity with operational state data validation and temporal consistency checks

Experience with graph data quality validation (Neo4j or similar)

Exposure to ML data quality (feature validation, training data quality)

Experience with data observability platforms

Exposure to industrial domains such as Manufacturing, Logistics, or Transportation is a plus