Location: Gurugram, India

CTC: Up to ₹30 LPA

Experience: 8–10 years preferred

Work Mode: Work from Office

Employment Type: Full-time

About the Role

We are looking for a Senior Data Quality SME / Solution Architect to lead Data Quality strategy, requirements translation, solution design, and delivery for enterprise client engagements.

The ideal candidate will work directly with client stakeholders/client proxies, understand complex business and data requirements, translate them into actionable Data Quality rules, and guide a small team of Data Quality Engineers to deliver the solution.

Experience with the specific Data Quality platform is not mandatory. Platform training, onboarding and certification will be provided. We are primarily looking for strong expertise in SQL, Data Quality/Data Testing, data modelling, enterprise data environments, troubleshooting, and client-facing solution design.

Key Responsibilities

Lead Data Quality requirements gathering with client stakeholders and translate business requirements into concrete rule designs.

Define and own the overall Data Quality and testing strategy across different data pipeline layers.

Design appropriate rules covering validation, duplicate detection, reconciliation, checksum, pushdown and script-based testing.

Determine the appropriate pipeline layer for each rule and avoid redundant or overlapping checks.

Define rule parameters including thresholds, severity, exception handling and routing.

Work closely with client engineering, data and business teams to understand data flows and quality requirements.

Present, explain and defend Data Quality logic and results to technical and non-technical stakeholders.

Act as the escalation point for complex Data Quality issues, job failures and platform-related problems.

Analyse logs, stack traces and query performance issues to identify root causes.

Guide engineering teams on resolution and provide clear technical escalations where required.

Lead and mentor a small team of Data Quality Engineers and ensure timely delivery against client timelines.





Identify scope creep, delivery risks and unrealistic sequencing and proactively communicate them to stakeholders.

Support platform architecture and configuration, including users, roles, workspaces, connections, notifications and related administration.

Ensure appropriate separation between active Data Quality testing, data cataloguing and upstream data governance.

Maintain high standards of documentation, rule inventories, exception handling and delivery processes.

Required Technical Skills

SQL – Must Have

Strong/advanced SQL skills with experience in enterprise databases.

Complex joins, CTEs and window functions.

Query optimisation and performance tuning.

Experience working with large-scale datasets.

Exposure to one or more of the following is preferred:

Snowflake

Oracle

SQL Server

Databricks / Databricks SQL

PostgreSQL

Teradata

Other enterprise-scale SQL environments

Data Quality & Data Testing

Strong practical understanding of

Data validation

Duplicate detection

Data reconciliation

Checksum/control-total validation

Cross-system validation

Exception handling

Threshold-based quality checks

Data Quality strategy and rule design

Data Modelling

Strong understanding of relational data models.

Star and snowflake schemas.

Normalised and denormalised data structures.

Primary and foreign key relationships.

Referential integrity.

Orphan-record detection.

Cross-system key reconciliation.

Enterprise Data

Experience working with large and complex enterprise data environments such as:

Data warehouses

Data lakes

Multi-layer data pipelines

Partitioned and incremental data

Slowly Changing Dimensions





Multi-source enterprise datasets

Experience with technologies such as SAP, Snowflake, Databricks, Microsoft Fabric/OneLake, Oracle, SQL Server or similar is an advantage.

Programming / Scripting

Python or Groovy scripting experience.

Ability to create or modify scripts used for Data Quality rules and workflow utilities.

Understanding of parameterisation, conditional workflows and automation is preferred.

Client & Leadership Skills

Strong client-facing communication and stakeholder management.

Ability to convert ambiguous business requirements into clear technical solutions.

Comfortable presenting Data Quality findings and explaining technical concepts to non-technical stakeholders.

Ability to lead and mentor a small team of Data Quality Engineers.

Strong ownership, reliability and problem-solving mindset.

Ability to identify delivery risks and manage priorities in a client workplace.

Platform Experience

Experience with a commercial Data Quality/Data Testing platform is preferred but not mandatory.

Candidates with strong SQL + Data Quality/Data Testing + enterprise data experience will be considered even if they have not worked on the specific platform.

Platform training, onboarding and certification will be provided.

Preferred Candidate Background

We are open to candidates from backgrounds such as:

Data Quality

Data Testing / ETL Testing

Data Governance

Data Engineering with strong hands-on Data Quality experience

Data Architecture with strong Data Quality exposure

Technology / Data Consulting

Industry and specific platform experience are flexible for candidates with strong relevant technical and client-facing experience.

Experience & Education

8–10 years of overall experience preferred.

Candidates with strong relevant experience can be considered irrespective of exact years.

Any graduate degree with strong relevant technical experience is acceptable.

B.Tech/B.E./M.Tech/MCA or equivalent technical backgrounds preferred.

📌 Senior Data Quality (Gurugram)
🏢 GoodSpace AI
📍 Gurugram