Consultant - Data Quality

We are seeking an experienced and highly skilled Data Quality SME & Lead Developer to be a crucial part of our upcoming 2026 data initiatives. This role requires deep expertise in implementing enterprise- level modernization programs and strategic initiatives in Data Governance, Data Catalog, and Data Quality. You will be instrumental in ensuring the reliability, accuracy, and completeness of our data assets across diverse platforms and technologies, playing a key role in enabling trusted data for downstream AI and Machine Learning applications. This role demands deep technical understanding, strong problem-solving skills, and the ability to drive complex data quality initiatives from conception to deployment, often interfacing and coordinating with other team members across India and the US.

Essential Responsibilities:

• Lead the design, development, and implementation of enterprise-level data quality frameworks and solutions.

• Translate complex business requirements and data governance policies into executable data quality rules, checks, and processes.

• Implement real-time data quality solutions and data observability leveraging tools such as Monte Carlo, Dynatrace, or custom solutions.

• Provide subject matter expertise in data quality, data observability concepts, and their practical application.

• Develop custom data quality solutions using SQL, Python, or other relevant programming languages when off-the-shelf tools are not sufficient.

• Design and optimize data quality checks across various data platforms and technologies, including modern data stacks (Spark, Scala, PySpark, Databricks, GCP Data services). and traditional ETL tools (Informatica BDM).

• Ensure data quality for various data storage solutions, including data lakes, data warehouses, SQL databases, and NoSQL databases.

• Utilize SQL extensively for data profiling, anomaly detection, and data quality checks.

• Document technical designs, data flows, and operational procedures thoroughly for data quality initiatives.

• Stay current with emerging trends and technologies in data management, data quality, data observability, Open Telemetry, Open Lineage, and cloud platforms.

• Collaborate with data architects, data engineers, data scientists, and business stakeholders to integrate data quality processes into existing data pipelines and ensure data readiness for AI and Machine Learning models.

• Apply expertise in Master Data Management, Data Governance, and Data Catalog concepts to enhance data quality.

• Troubleshoot and resolve complex data quality issues, identifying root causes and implementing sustainable solutions.

• Potentially mentor junior team members and contribute to best practices within the data management team.