Data Governence

Roles & Responsibilities:-

1. Develop and maintain enterprise data governance strategies, policies, and standards aligned with business goals
2. Manage Microsoft Purview accounts, collections, and RBAC; optimize for large-scale environments (50TB+)
3. Design metadata repositories and maintain business glossaries and data dictionaries
4. Implement ingestion workflows via ADF, REST APIs, PowerShell, Azure Functions
5. Define classification rules and sensitivity labels (PII, PCI, PHI); integrate with MIP, DLP, Insider Risk Management
6. Define KPIs and dashboards to monitor data quality across domains
7. Maintain business glossary with domain owners and stewards; enforce approval workflows
8. Automate governance processes using PowerShell, Azure Functions, Logic Apps
9. Set up dashboards for audit logs, compliance reporting, and metadata coverage
10. Collaborate across business, IT, legal, and compliance teams for role alignment

Ideal Candidate:-

1. Strong Data Governance Lead Profile with deep Microsoft Purview and enterprise governance expertise
2. Mandatory (Experience 1): Must have 7+ years of experience in data governance and data management with at least the recent 3+ years of exposure in Microsoft Purview
3. Mandatory (Experience 2): Must have experience defining, leading, and operationalizing an enterprise data governance framework — strategy, policies, and standards aligned to business goals and regulatory compliance.
4. Mandatory (Tech skill 1): Must be proficient in Microsoft Purview — accounts, collections, RBAC, classification/labelling, DLP, Unified Catalog, Data Map, eDiscovery, Compliance Manager, and lifecycle/records management (ideally at large scale, 50TB+).
5. Mandatory (Tech skill 2): Must be strong in metadata management, lineage mapping (e.g. ADF → Synapse → Power BI), data classification, and security governance (PII/PCI/PHI, sensitivity labels, MIP/DLP)
6. Mandatory (Tech skill 3): Must have experience with data governance tools such as Informatica (Axon), Collibra, Atlan, or IBM IG Catalog.
7. Mandatory (Tech skill 4): Must have experience integrating governance with the Azure data stack (Data Lake, Synapse, SQL DB, Power BI) and Snowflake, and automating via ADF, REST APIs, PowerShell, Azure Functions / Logic Apps.
8. Mandatory (Tech skill 5): Must have experience defining data quality KPIs/dashboards, remediation workflows, and business glossary/stewardship (domain owners, approval workflows, metadata audits)
9. Mandatory (Compliance): Must have strong knowledge of GDPR, CCPA, HIPAA, and SOX compliance requirements.
10. Mandatory (Skill): Must be able to bridge technical governance with business and compliance goals, collaborating across business, IT, legal, and compliance teams, and driving governance training and change management
11. Mandatory (Company): B2B Tech/Consulting/B2B Software

We are hiring a Senior Data Governance Manager with 5+ years of data-management experience to define and run enterprise data governance policy, quality, metadata, lineage, and cataloging so the business can trust and safely use its data.

Key Responsibilities

• Define and enforce data governance policies and standards

• Own data quality frameworks, monitoring, and remediation

• Manage metadata, data lineage, and cataloging

• Drive master data management (MDM) practices

• Ensure compliance with privacy/regulatory requirements

• Align business and technical stakeholders on standards

Mandatory Skills

• 5+ years in data management with governance ownership

• Data governance frameworks and policy

• Data quality and master data management

• Metadata management and data cataloging

• Strong SQL and data-platform understanding

• Stakeholder alignment and compliance

Nice to Have: Collibra/Informatica/Alation; cloud data platforms (Snowflake, Azure, GCP)

Years of Exp: 5 to 8 Years (Relevant 5+ Years)

Location: Hyderabad

Notice Period: Immediate to 20 days

Offshore: Data Governance Analyst

Position Summary

Execute day-to-day Data Governance activities for RTB initiatives under the direction of the Onshore Lead. The role will focus on producing accurate, complete, and traceable governance artifacts that support enterprise standards, control requirements, and audit readiness.

Key Responsibilities

Register and maintain data assets, reports, and data products in Collibra and Data Marketplace.

Capture and validate business, technical, and operational metadata.

Document end-to-end data lineage, including sources, targets, transformations, and data movement.

Support business glossary, data classification, ownership, stewardship, and authoritative source documentation.

Assist with data quality rule documentation, issue tracking, and remediation follow-up.

Coordinate with data owners, engineers, architects, and application teams to resolve documentation gaps.

Maintain governance evidence, decisions, status reports, and action items.

Track work through Jira and escalate blockers promptly to the Onshore Lead.

Support multiple RTB workstreams while meeting established quality and delivery expectations.

Required Qualifications

Experience in Data Governance, Data Management, metadata management, lineage, or data quality.

Working knowledge of Collibra or a comparable governance platform.

Understanding of data warehousing, data modeling, ETL/data pipelines, and system-to-system data flows.

SQL proficiency and familiarity with cloud data platforms, preferably Snowflake.

Strong analytical, documentation, communication, and organizational skills.

Ability to work effectively in an onshore-offshore delivery model.

Preferred Qualifications

Experience with Collibra or similar Data Governance Platforms, Jira, Confluence, Cloud Data Solutions, Excel

Financial-services or regulated-industry experience.

Familiarity with Agile delivery and audit or regulatory documentation.

Key Responsibilities

• Lead end-to-end data migration initiatives, including assessment, planning, mapping, transformation, validation, and reconciliation.
• Define and implement data governance frameworks, standards, policies, and processes.
• Design and manage data solutions using Microsoft Azure Data Services.
• Lead development of BI dashboards, reports, KPIs, and analytics solutions.
• Work with business and technical stakeholders to understand reporting and data requirements.
• Develop and maintain data models, data pipelines, ETL/ELT processes, and reporting architecture.
• Ensure data quality, consistency, integrity, security, and compliance throughout migration and reporting processes.
• Identify data risks, dependencies, gaps, and migration challenges and drive their resolution.
• Establish data validation and reconciliation mechanisms to ensure migration accuracy.
• Provide technical leadership and guidance to data engineers, BI developers, and other project team members.
• Collaborate with application, cloud, infrastructure, and business teams during project implementation.
• Monitor data migration and BI deliverables against project timelines, quality standards, and business objectives.
• Prepare technical documentation, data dictionaries, mapping documents, governance guidelines, and project reports.

Required Skills & Experience

• 7+ years of experience in data, migration, BI, or related technology roles.
• Strong experience working on software/IT projects and managing data-related workstreams.
• Hands-on experience with Microsoft Azure Data Services.
• Strong understanding of data migration methodologies, ETL/ELT, data transformation, and reconciliation.
• Experience in Data Governance, Data Quality, Master Data, Metadata Management, and Data Security.
• Strong experience with BI reporting and dashboard development.
• Good understanding of SQL and relational databases.
• Experience with Power BI and data visualization is highly desirable.
• Knowledge of Azure services such as Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure SQL Database, or equivalent.
• Strong understanding of data architecture and data lifecycle management.
• Excellent stakeholder management, communication, analytical, and problem-solving skills.

IMMEDIATE JOINERS ONLY

Key Responsibilities:

1                   Data Flow Mapping & Lineage

2                   Design and produce end-to-end data flow maps for critical data items – from market source/core systems, through Data Lake staging, zone 2 and consumption zone 3, to downstream reporting, dashboards and analytics use cases.

3                   Document data lineage and transformations for critical data elements identified in the Master Data Requirements exercise, ensuring traceability that is audit-defensible and supports regulatory, governance and AI-readiness needs.

4                   Map data availability by country/Data Lake against the Product Hierarchy (to profit-centre level), building the consolidated Commercial Data Landscape view of what exists, where it sits (source only, staging, or consumption) and what is not captured at all.

5                   Document cross-system dependencies and cross-border data flows, flagging data residency, privacy and regulatory considerations to the appropriate governance forums.

6                   Data Inventory, Data Model Alignment & Gap Analysis

•                    Own and mature the data asset inventory, catalogue and data dictionary aligned to the consolidated Master Data Requirements Template – resolving “Not Specified”, “TBD” and “validation required” availability statuses through structured validation with Market IT and Data Engineering.

•                    Align business data requirements to the conceptual and logical data model of the target Data Lakehouse, ensuring the dependency between data model design and lineage tracking of critical data items is explicitly documented.

•                    Perform gap and hydration analysis by market and product, quantifying the scale of data that must be brought into the Data Lakes and providing sizing input to the Data Foundation Lead, DAE architects and Data Engineering delivery plans.

•                    Contribute to the Data Consolidation Plan towards a single source of truth, including recommended sequencing based on business priority (Top 200 fields, Horizon 1–3 priorities).

•                    Stakeholder Engagement & Workshops

•                    Work hand-in-hand with the Data Foundation Lead, Data & Analytics Programme Manager, Data Engineers, DAE/infrastructure architects, Local Market IT and Business stakeholders (Regional and Market) as the connective tissue between business data needs and technical implementation.

•                    Plan and facilitate structured interviews and cross-functional validation workshops with business, technology and data stakeholders to corroborate actual operating data flows against documented processes – establishing a fact-based, evidence-backed view rather than relying on documentation alone.

•                    Translate ambiguous business asks into clear data definitions, mapping rules and acceptance criteria that Data Engineering can build against, and play back findings to senior stakeholders in clear, visual, decision-oriented formats.

•                    Manage competing priorities across multiple markets with tact, keeping momentum in an environment of constrained capacity and differing local system landscapes.

•                    Governance, Ownership & Documentation

•                    Produce and maintain the Data Ownership & Accountability Matrix – mapping data owners, stewards and custodians per data asset and highlighting ownership gaps for remediation.

•                    Classify data assets by sensitivity and business function, aligning to Data Protection Policy, PDPA and applicable regulatory expectations (e.g. MAS guidelines) in partnership with Risk & Compliance.

•                    Ensure all data flow maps, lineage records and inventory artefacts are version-controlled, audit-ready and handed over cleanly into BAU data governance processes.

•                    Produce source to Datalake mapping document and data catalogue for missing data elements to complete Datalake hydration

Key Skills

•                    Data flow mapping and lineage documentation – proven ability to draw clear, accurate source-to-consumption data flow maps across complex multi-system, multi-market landscapes.

•                    Data architecture and modelling – strong grasp of conceptual/logical data models, data lake/lakehouse zone architectures (staging, conformed, consumption), data marts and MDM concepts.

•                    Data inventory, catalogue, dictionary and metadata management; familiarity with lineage/catalogue tooling (e.g. Purview, Collibra) and diagramming tools (e.g. Visio, ErWin, Lucidchart).

•                    Hands-on data profiling and validation skills (SQL essential) to verify what actually exists in source systems and lake zones.

•                    Strong stakeholder management – this is critical: able to build trust and drive outcomes across regional leadership, market business teams, Market IT and engineering, and to facilitate effective cross-functional workshops.

•                    Insurance domain knowledge – ideally commercial and specialty lines, with an understanding of policy, claims, reinsurance and underwriting data.

•                    Data quality, governance and privacy concepts, including cross-border data considerations.

•                    Clear written and visual communication – able to make complex data landscapes understandable to executives.

Experience & Qualification Requirements:

•                    8+ years’ experience in data architecture, data business analysis or information architecture roles, with at least:

•                    3+ years documenting data flows, lineage or data landscapes across multi-system / multi-market environments.

•                    Experience in Insurance or Financial Services, ideally within data foundation, data lake or data governance programmes.

•                    Demonstrated delivery of data inventory / data mapping / current-state data landscape assessments involving both business and IT stakeholders.

•                    Relevant certification (e.g. DAMA CDMP, TOGAF, cloud data platform certifications) preferred.

Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration

Job Summary

We are seeking a skilled and detail-oriented Power BI Developer to design, develop, and maintain enterprise-level BI solutions. The ideal candidate should have strong expertise in Power BI, DAX, SQL, Data Modeling, and performance optimization tools such as DAX Studio, Tabular Editor, and ALM Toolkit. The candidate will collaborate with business stakeholders to transform data into actionable insights and deliver high-quality dashboards and reports.

Key Responsibilities

• Design, develop, and maintain interactive Power BI dashboards and reports.
• Create complex DAX measures, calculated columns, and calculated tables to meet business requirements.
• Develop and optimize SQL queries, stored procedures, views, and ETL processes.
• Design and implement scalable Star Schema and Snowflake Data Models.
• Perform report and model performance tuning using DAX Studio.
• Utilize Tabular Editor for model management, calculation groups, best practice analysis, and metadata enhancements.
• Manage model deployment, comparison, and version control using ALM Toolkit.
• Configure and manage Power BI Workspaces, Apps, Gateways, and Security (RLS/OLS).
• Work extensively with Power BI Service/Web Experience, including dataset refresh schedules, deployment pipelines, subscriptions, and workspace administration.
• Collaborate with business users to gather and analyze reporting requirements.
• Ensure data accuracy, governance, security, and report performance.
• Troubleshoot data-related issues and implement effective solutions.
• Create technical documentation and provide knowledge transfer to support teams.

Required Skills

Technical Skills

• Strong experience in Microsoft Power BI Development.
• Expertise in DAX (Data Analysis Expressions).
• Advanced knowledge of SQL Server/T-SQL and query optimization.
• Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Fact & Dimension Tables).
• Hands-on experience with Tabular Editor.
• Experience using DAX Studio for model and query performance tuning.
• Experience with ALM Toolkit for model comparison and deployment.
• Strong understanding of Power BI Service/Web Experience.
• Knowledge of Power Query (M Language).
• Experience with Row-Level Security (RLS) and data governance.
• Understanding of data warehousing and ETL concepts.

We are hiring a Data Architect to design scalable, well-governed data platforms.

Responsibilities

• Design enterprise data models, warehouses and lakehouse architecture
• Define standards for data integration, quality and governance
• Guide data engineering teams on pipelines and tooling choices
• Align data architecture with business and analytics needs

Requirements

• 5+ years in data engineering or architecture
• Strong data modeling and SQL expertise
• Experience with a cloud data platform (Snowflake, Databricks, BigQuery or Redshift)

Job Description

• Design and Implement Data Solutions: Lead the design, development, and implementation of scalable and secure Azure-

based data platforms, ensuring integration with various data sources and business systems. Deliver at least 2 major

projects every year with a focus on data engineering best practices.

• Optimize Data Pipelines: Build and optimize end-to-end data pipelines using Azure Data Factory, Azure Databricks, and

Azure Synapse, with an emphasis on automating data workflows. Achieve a 20% reduction in pipeline execution times

within the first 6 months.

• Cloud Infrastructure Management: Manage and maintain the Azure data environment, ensuring high availability, disaster

recovery, and cost optimization. Track and improve system uptime to exceed 99.9% reliability.

• Collaborate with Cross-Functional Teams: Partner with data scientists, data analysts, and business stakeholders to translate

business requirements into efficient data solutions. Facilitate at least 3 collaborative sessions per quarter to address key

business use cases.

• Ensure Data Security & Compliance: Implement data security measures, ensuring compliance with industry regulations

(GDPR, HIPAA, etc.) and company policies. Achieve and maintain full compliance in all data environments within the first

quarter of onboarding.

• Continuous Learning & Knowledge Sharing: Stay up-to-date with emerging Azure technologies, and mentor junior

engineers to promote knowledge sharing. Complete 1 Azure certification annually and conduct at least 2 internal

knowledge-sharing sessions per year.

• Sound knowledge of data governance practices, data quality management, and data security principles.

• Play a pivotal role in shaping our organization's data-driven journey, driving innovation through data analytics and insights.

• Optimize data storage, processing and retrieval mechanisms for performance, cost, and scalability using data storage

services (such as Azure Data Lake Storage, Azure SQL Database, etc.), data processing services (such as Azure Data Bricks,

Azure Synapse, etc.) and data visualization (PowerBI, Qlik, etc.) & integration services (Data API builder, logic apps, etc.)

• Monitor and troubleshoot data platform performance, identify and resolve issues, and provide recommendations for

continuous improvement.

• Collaborate with DevOps teams to automate deployment, configuration, and monitoring processes using Azure DevOps,

PowerShell, or other relevant tools.

• Stay up to date with the latest trends and advancements in cloud data services and provide recommendations on adopting

new technologies or features to enhance the data platform.

• Document technical designs, procedures, and guidelines for data platform engineering and operations

Knowledge, Skills & Experience

Job Experience • Bachelor's degree in Computer Science, Engineering, or a related field. Advanced

degree preferred.

• Proven 6-10 years experience in playing platform engineer or admin role

• Experience with big data technologies such as Apache Spark, Hadoop, or similar

frameworks.

• Solid understanding of cloud computing concepts and experience with cloud

infrastructure management and provisioning.

• Solid understanding of network security concepts and technologies (such as

firewalls, VPNs, intrusion detection/prevention systems, etc.) and data security

concepts and technologies (such as access controls, encryption, observability,

privacy laws/regulations, etc.)

• Experience in a Retail setup is preferred.

Required Skills The position will require someone with the following:

• Strategic Planning

Public

• Communication and Collaboration

• Problem Solving Skills A/B testing & experimentation

• SQL, BI tools, and storytelling with data

We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.

Qualifications and Skills:

• Minimum 5 years of experience as a Data Engineer
• Hands-on experience with Azure cloud-based data solutions
• Fabric experience is a must – designing, implementing, and managing data workflows and pipelines
• Expertise in database design and management, including SQL databases such as SQL Server
• Proficient in ETL (Extract, Transform, Load) design for data integration and processing
• Strong knowledge of data modeling principles and techniques
• Experience with Azure Data Factory (ADF) for orchestrating data workflows
• Ability to analyze and translate data into actionable insights, reports, and visualizations
• Proficiency in Power BI for reporting and data visualization
• 
  

Desirable Skills:

• Experience with Power BI Report Builder / Reporting Services
• Knowledge of statistical analysis or Data Science
• Experience within the UK Insurance industry is a plus
• Python or R coding skills

Responsibilities:

• Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
• Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
• Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
• Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
• Implement different methods of streaming data and create reconciliations for datasets
• Build analytical models to support reporting and analytics
• Collaborate with an agile delivery team to work on the backlog of specified work