Cloud Data Architect

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.

About the Role

We are looking for an experienced Power BI Architect to lead enterprise-wide BI initiatives. This role will be responsible for designing, implementing, and governing scalable Power BI solutions across the organization. The ideal candidate will play a key role in establishing best practices, driving adoption, and owning the overall BI architecture within the Center of Excellence (CoE).

Key Responsibilities

• Lead end-to-end implementation of Power BI solutions across the enterprise
• Design scalable, secure, and high-performance BI architecture
• Act as the Power BI Architect, providing technical leadership and direction
• Own and drive BI governance, standards, and best practices within the CoE
• Collaborate with business and technology teams to translate requirements into robust BI solutions
• Define data modeling strategies, reporting frameworks, and dashboard standards
• Ensure data accuracy, consistency, and performance optimization across reports
• Support and guide development teams in Power BI implementation
• Enable enterprise-wide adoption of Power BI through training, documentation, and mentorship
• Work closely with IT/technology teams to integrate Power BI with data platforms and enterprise systems

Required Skills & Qualifications

• 10+ years of experience in BI/Data Analytics, with strong focus on Power BI
• Proven experience in enterprise-wide Power BI implementation
• Strong expertise in:
• Power BI (Desktop, Service, Gateway, Dataflows)
• Data Modeling (Star Schema, Snowflake Schema)
• DAX, Power Query (M language)
• Experience in designing and implementing BI architecture at scale
• Strong understanding of data warehousing concepts and ETL processes
• Experience working within a Center of Excellence (CoE) model
• Excellent stakeholder management and communication skills

Preferred Skills

• Experience with Azure (Azure Synapse, Data Factory, Data Lake)
• Knowledge of DevOps practices for Power BI (CI/CD pipelines)
• Exposure to governance tools and security frameworks
• Certification in Power BI / Microsoft Data Platform

Solution Architect – AZURE Data Engineering

Job Overview

We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.

Key Responsibilities

• Design and implement scalable data architecture and solutions.
• Develop and manage Data Warehouse and Data Lake architectures.
• Design data platforms using Medallion Architecture.
• Lead Data Engineering and ETL activities.
• Work with Azure Synapse Analytics for data processing and analytics.
• Develop data solutions using PySpark / Apache Spark.
• Define and implement data validation and data quality processes.
• Collaborate with business, data, and technology teams to deliver effective data solutions.

Required Skills

• Strong experience in Solution Architecture / Data Architecture.
• Strong knowledge of Data Warehouse and Data Lake architecture.
• Good understanding of Medallion Architecture.
• Strong experience in Data Engineering and ETL.
• Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
• Strong knowledge of PySpark / Apache Spark.
• Experience with Data Validation and Data Quality.
• Good communication and stakeholder management skills.
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Experience

8+ Years

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.

At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available.

For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.

As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work!

Job Overview 

Principal Data Engineer

About Engineering at Mitratech Legal Solutions 

Mitratech's engineering organization is a collaborative and dynamic environment where engineers are empowered to drive technical direction and innovation. Our engineers are passionate about delivering high-quality products and solutions that meet the evolving needs of our customers, and we're committed to fostering a culture of continuous learning and growth. 

About the Role 

Mitratech is a fast-paced and dynamic environment, and this role requires someone who is adaptable, resilient, and able to thrive in a rapidly changing landscape. If you’re a seasoned engineer with a passion for technical leadership, innovation, and collaboration — including building the data foundations that power trusted reporting and agentic AI-driven products — we’d love to hear from you. 

What You Will Do

•  Drive technical direction for a significant product domain or platform capability, ensuring alignment with business objectives and customer needs 

•  Design and maintain data pipelines and reporting models that power trusted business metrics and increasingly feed agentic AI systems (e.g., RAG ingestion, embeddings, vector stores, AI agent workflows) 

•  Use AI-assisted and agentic engineering tools (e.g., Claude Code, Copilot, Cursor, AI agents) as part of your own workflow, and help other engineers adopt agentic development practices effectively 

•  Reduce systemic complexity by identifying and leading architectural debt remediation, and developing strategies for ongoing technical debt management 

•  Partner with Product and Engineering leadership to inform multi-quarter roadmap feasibility, and provide technical guidance and oversight to ensure successful implementation 

•  Elevate engineering craft across multiple teams through RFCs, mentorship, and knowledge sharing, and develop training programs to improve engineering skills and knowledge 

•  Represent Mitratech’s technical capabilities externally, including speaking at conferences, contributing to open-source projects, and engaging with industry peers and thought leaders 

What We Are Looking For 

To be successful in this role, you will need: 

•  10+ years of experience in software engineering, with a focus on technical leadership and architecture 

•  Deep understanding of data engineering principles, including data modeling, data warehousing, reporting, and data governance 

•  Strong technical expertise in SQL, PostgreSQL, ETL/ELT pipelines, BI tools, and analytics platforms 

•  Practical experience with AI/LLM-adjacent and agentic AI data work — e.g., RAG ingestion pipelines, embedding generation, vector store management, or building/operating AI agent workflows over data — using AI coding assistants (Claude Code, Copilot, Cursor, or similar) as a regular part of the engineering workflow 

•  Working knowledge of modern cloud platforms such as AWS 

•  Experience with BI, reporting, dashboards, and customer-facing analytics 

•  Experience leading cross-functional initiatives with product, engineering, analytics, and business teams 

Nice to Have 

•  Working knowledge of Ruby on Rails and React 

•  Experience with a semantic or metrics layer (e.g., dbt Semantic Layer, headless BI) 

•  Understanding of CI/CD, Git-based workflows, and infrastructure-as-code 

The Stack Context 

•  Modern data stack: Fivetran, Airbyte, dbt, Snowflake, GitHub, Terraform, or similar tools 

•  Application context (nice to have): Ruby on Rails, React, or similar backend/frontend frameworks 

•  Data modeling: SQL, analytics models, documentation, testing, naming standards, and version control 

•  Infrastructure: cloud-based data infrastructure, infrastructure-as-code, CI/CD, monitoring, and cloud storage 

•  Data workflows: ingestion, transformation, orchestration, reporting, deployment, and change management 

•  Reporting focus: trusted metrics, scalable reporting models, dashboards, exports, and data quality 

•  AI surface: data pipelines and quality practices supporting AI/LLM and agentic AI use cases (RAG, embeddings, vector stores, AI agents) alongside traditional BI 

Why This Role 

This role offers a unique opportunity to drive technical direction and innovation at a rapidly growing company, while also mentoring and coaching engineers to improve their craft. As a Principal Data Engineer at Mitratech, you will have the chance to work on complex and challenging problems spanning trusted reporting and agentic AI systems, collaborate with cross-functional teams, and represent the company's technical capabilities externally. If you're looking for a role that offers a mix of technical leadership, data and reporting depth, agentic AI innovation, and collaboration, this could be the perfect fit for you. 

We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.

Job Description:

Experience: 10+ Years

Job Summary

We are looking for an experienced Azure Fabric Data Architect to lead the design and implementation of an enterprise data platform on Microsoft Fabric. The role involves architecting scalable data solutions, defining data governance, and enabling AI-driven analytics for a global financial services client.

Key Responsibilities

• Design end-to-end data architecture using Microsoft Fabric.
• Build enterprise Lakehouse, Data Warehouse, and OneLake solutions.
• Define data ingestion, ETL/ELT, governance, security, and performance strategies.
• Lead architecture for AI-powered analytics, AI Agents, and enterprise chatbots using Azure AI services.
• Work with business stakeholders to translate requirements into technical solutions.
• Mentor engineering teams and provide technical leadership.

Required Skills

• Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, OneLake)
• Azure Data Engineering
• Power BI
• Azure AI Services / Azure OpenAI
• Data Architecture & Data Modeling
• SQL, Python
• Azure DevOps, CI/CD
• Strong stakeholder management and solution design experience
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Preferred: Experience in Capital Markets or Financial Services and Microsoft Azure/Fabric certifications.

NOTE: One technical round is mandatory to be taken F2F from office.

We are looking for a Lead Data Architect to design, build, and scale our data pipelines and entity resolution systems. This role combines deep technical expertise in data engineering with hands-on experience in AI-assisted tooling, entity matching, and data integration from diverse sources. You will lead architectural decisions for our data platform, mentor engineers, and ensure our pipelines are reliable, scalable, and production-grade.

Key Responsibilities

     Architect, build, and maintain robust, scalable data pipelines that ingest, transform, and serve data from multiple internal and external sources.

     Own the end-to-end orchestration of data workflows using tools like Dagster, ensuring observability, reliability, and maintainability of pipelines.

     Design and implement entity resolution workflows — including matching, merging, and survivorship logic — using tools such as Splink, to produce clean, deduplicated, golden records.

     Build and maintain web scrapers to source data from external providers, ensuring resilience to source changes, rate limits, and data quality issues.

     Integrate and reconcile data coming from multiple, often inconsistent, sources into unified, trustworthy datasets.

     Design and maintain data models and schemas across transactional and analytical systems, ensuring consistency, scalability, and performance.

     Leverage AI/LLM-based tools and techniques to enhance data pipeline capabilities — e.g., intelligent data extraction, automated data quality checks, or AI-assisted entity matching.

     Define and enforce best practices around pipeline design, testing, monitoring, and documentation.

     Collaborate closely with data engineers, product managers, and other stakeholders to translate business requirements into scalable data architecture.

     Provide technical leadership and mentorship to the data engineering team.

Required Skills & Experience

     Strong hands-on experience building and maintaining production-grade data pipelines at scale.

     Practical experience with Dagster (or similar orchestration tools like Airflow/Prefect) for pipeline orchestration.

     Experience with Splink or similar probabilistic/deterministic record linkage tools for entity matching, merging, and survivorship.

     Strong proficiency in Python, including experience writing and maintaining web scrapers.

     Proven experience integrating and maintaining data pipelines that pull from multiple, heterogeneous data sources.

     Experience applying AI/ML tools within data engineering workflows (e.g., LLM-assisted data cleaning, extraction, or matching).

     Hands-on experience with relational and distributed databases such as PostgreSQL and Google Cloud Spanner.

     Strong understanding of data modeling principles (normalization, dimensional modeling, schema design) across OLTP and OLAP systems.

     Experience with cloud data warehousing platforms such as BigQuery, Redshift, and cloud platforms (GCP/AWS/Azure).

     Strong communication skills and experience working cross-functionally with engineering and product teams.

     Experience with distributed data processing frameworks (e.g., Spark, Dask).

     Familiarity with data governance, lineage, and cataloging tools.

     Prior experience in a lead or architect-level role guiding a data engineering team.

What We're Looking For

A technically strong, hands-on leader who can balance architectural thinking with the practical grit of debugging a flaky scraper or tuning a matching algorithm — someone who's comfortable owning both the big picture and the messy details of real-world data.

Next

Job Title: Senior Data Engineer

Position Summary

We are seeking a highly skilled Data Engineer with strong expertise in reporting infrastructure, data modeling, and analytics platforms. This role will focus on building scalable reporting solutions, optimizing data pipelines, and enabling data-driven decision-making across the organization. The ideal candidate will have deep experience with databases, data warehousing, and complex query development. While Ruby on Rails experience is beneficial, the primary emphasis is on data engineering and reporting systems.

Key Responsibilities

• Design, develop, and maintain reporting infrastructure and data platforms.
• Build and optimize complex SQL queries, data models, and reporting datasets.
• Develop scalable ETL/ELT pipelines and data integration processes.
• Design and maintain database schemas to support analytics and reporting requirements.
• Collaborate with business stakeholders to understand reporting needs and translate them into technical solutions.
• Implement data quality, governance, and performance best practices.
• Support and enhance enterprise reporting solutions and dashboards.
• Work with large-scale datasets in cloud data warehouse environments.
• Troubleshoot reporting issues and optimize database performance.
• Partner with engineering and product teams to establish sustainable data architecture.

Must Have: Technical Skills

• PostgreSQL
• Snowflake
• Advanced SQL
• Data Modeling
• Data Warehousing
• Reporting & Analytics Infrastructure
• ETL/ELT Development
• Query Performance Tuning

Success Profile:

The ideal candidate is a data-focused engineer who enjoys working with complex datasets, designing scalable reporting solutions, and building foundational infrastructure that empowers analytics and business intelligence teams. They should be comfortable navigating databases, optimizing queries, and translating business reporting needs into robust technical implementations.

Experience Range: 5-10 years

Role Type: Individual Contributor / Senior Engineer

Primary Focus: Reporting Infrastructure, Data Engineering, Data Warehousing, and Analytics Enablement.

Job Summary

The Technical Lead will be responsible for overseeing and leading projects related to Azure Data Factory (ADF), Azure Databricks, SQL, Oracle PL/SQL, and Python. The role involves designing, developing, and implementing data solutions while ensuring they meet the business requirements and align with best practices. (1.) Key Responsibilities

1. Lead and manage end-to-end data engineering projects using azure data factory, azure databricks, sql, oracle pl/sql, and python.

2. Collaborate with stakeholders to gather and understand requirements for data pipelines and analytics solutions.

3. Design and develop etl processes, data models, and data integration solutions.

4. Provide technical guidance and mentorship to the team members.

5. Ensure data quality, data governance, and data security standards are maintained throughout the project lifecycle.

6. Troubleshoot and optimize data pipelines and processes for performance and efficiency.

7. Stay updated on the latest trends and technologies in data engineering and contribute to continuous improvement efforts.

Skill Requirements

1. Proficiency in azure data factory (adf) and azure databricks for building and managing data pipelines.

2. Strong experience with sql and oracle pl/sql for data querying and manipulation.

3. Advanced programming skills in python for scripting and data processing tasks.

4. Knowledge of data modeling, data warehousing concepts, and database design principles.

5. Ability to work in a collaborative team environment and communicate effectively with stakeholders.

6. Strong analytical and problem-solving skills with attention to detail.

7. Experience in data visualization tools and techniques is a plus.

Certifications: Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle PL/SQL, or Python are advantageous.

Skill (Primary)

Data Fabric-Azure-Azure Data Factory (ADF)