Data Analyst - II

Techila Global; Mumbai; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

Techila Global in Mumbai seeks a senior data governance and quality lead to define data quality rules and monitor lineage for AI agents. You will collaborate with data engineers and ensure compliance with privacy regulations while maintaining catalogs and semantic layers.

You will drive data governance policies, mentor teams, and ensure secure, auditable data used in autonomous AI systems across platforms.

Qualifications

• Bachelor's degree with 8–10 years total experience required.
• Strong SQL and Python for data processing expected.
• Experience in data governance, data modeling and validation frameworks.
• Knowledge of data analysis, visualization, observability and lineage is preferred.
• Exposure to Agile methodologies and modern DB tech is beneficial.

Responsibilities

• Define and implement data quality rules and schema validation for AI data.
• Collaborate with Data Engineers to monitor data quality metrics and lineage across ingestion pipelines.
• Establish audit trails and compliance for data used by AI agents, ensuring GDPR/CCPA/HIPAA considerations.
• Maintain data catalogs and semantic layers; enforce access controls and PII handling.
• Serve as primary liaison between AI/ML teams, Legal/Compliance and business owners.

Skills

SQL

Python

Data modeling

Schema design

Data validation

Data governance

Data analysis

Data visualization

Data observability

Data versioning

End-to-end process

Data lineage

Agile methodologies

Database technologies

Communication

Attention to detail

Education

Bachelor's degree

Tools

GCP

Cloud

Job description

KEY ACCOUNTABILITIES

Define and implement data quality rules (schema validation, referential integrity, distribution checks, drift detection) using Data Quality tools.Collaborate with Data Engineers to define and monitor data quality metrics (accuracy, completeness, consistency) essential for high-performing, unbiased AI agents and their tools.Monitor dataset health metrics (null ratios, entropy, cardinality, outliers) and set up alerting mechanisms.Implement end-to-end data lineage across ingestion transformation feature stores model inputs agent outputs.Use observability tools (Monte Carlo, etc) to trace data dependencies impacting agent decisionsSupport root cause analysis of agent failures linked to upstream data issues.Serve as the primary point of contact between AI/ML Engineers, Data Scientists, Legal/Compliance, and Business Process Owners regarding all data-related aspects of Agentic AI solutions.Maintain data catalogs and semantic layers (Collibra, Alation, etc)Ensure interoperability across structured data and unstructured data.Ensure all data practices related to Agentic AI comply with internal policies and external regulations (e.g., GDPR, CCPA, HIPAA), paying close attention to the unique compliance risks of autonomous data useEstablish and enforce data governance policies, standards, and procedures uniquely tailored for AI agents, including data collection, usage, sharing, and retention protocols specific to autonomous and multi-agent systems.Enforce data access controls, masking, and PII handling in accordance with regulations.Maintain audit trails for data used in agent decisions (critical for explainability and compliance).Develop and execute procedures for Annual Attestation for Unstructured Data Management Plans (DMP) and Agentic AI Data Management Plans (ADMPs)Support DMP/ADMP automation initiatives across BQ, Agentic AI, and other applicable areas of data governanceEstablish audit compliance methodology and communication processes (e.g., all data sources/agents have DMP/ADMP, cataloguing of all AI agents, attestation completion)

MINIMUM QUALIFICATIONS

Bachelor's degree and 8-10 years of total experience

PREFERRED QUALIFICATIONS

Strong SQL and working knowledge of Python for data processingExperience with Data Modeling, schema design and data validation frameworks.Demonstrated knowledge of Data Governance strategies and processesExperience with Data Analysis, Data Visualization, Data Observability, Data versioning, End to End Process mindset, Lineage.Exposure to Database Technologies (GCP, Cloud, etc)Exposure to Agile Methodologies (ADO, etc)Demonstrated ability to influence and drive change within their domainSolid communication and interpersonal skillsExperience and competence in leading, influencing, coaching and mentoring othersAttention to detail with the ability to identify patterns and inconsistencies