Collibra - Bengaluru Location - (F2F Interview 0n 7th-Aug-2026)

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.

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)

Company Name – Wissen Technology

Group of companies in India – Wissen Technology & Wissen Infotech

Work Location – Whitefield, Bangalore

Website and Company profile:

www.wissen.com

LinkedIn Page:

https://www.linkedin.com/company/wissen-technology/

While you may already know about Wissen and the company history, here is a quick rundown for you.

About Wissen Technology:

·    The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.

·    Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.

·    Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.

·    Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.

·    Globally present with offices US, India, UK, Australia, Mexico, and Canada.

·    We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.

·    Wissen Technology has been certified as a Great Place to Work®.

·    Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.

·    Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.

·    We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.

About Role :

Key Responsibilities

• Build and maintain data transformation pipelines using java Spark
• Develop and optimize large-scale/CPU intensive data processing using Apache Spark
• Orchestrate workflows using Airflow
• Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage
• Support schema evolution, backfills, and incremental processing
• Ensure pipelines meet SLAs for freshness, reliability, and performance
• Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)

Required Skills & Qualifications

• Strong hands-on experience with 
• HBase
• Apache Spark
• Experience with HBase or similar lakehouse query engines
• Airflow 
• Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)
• Proficiency in Java
• Experience with Git-based development and CI/CD

Nice-to-Have Skills

• OpenTable format/Iceberg ,Apache Arrow
• CDC-based analytics pipelines
• Cloud platforms (AWS)
• Kubernetes-based data platforms

Key Responsibilities

Build and maintain data transformation pipelines using java Spark

Develop and optimize large-scale/CPU intensive data processing using Apache Spark

Orchestrate workflows using Airflow

Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage

Support schema evolution, backfills, and incremental processing

Ensure pipelines meet SLAs for freshness, reliability, and performance

Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)

Required Skills & Qualifications

Strong hands-on experience with Apache Spark

Experience with HBase/SQL or similar lakehouse query engines

Airflow 

Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)

Proficiency in Java

Experience with Git-based development and CI/CD

Job Description

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop data processing solutions using Python.
• Write complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain data ingestion and integration workflows.
• Implement data quality, validation, monitoring, and error-handling processes.
• Develop and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
• Collaborate with data analysts, data scientists, software engineers, and business teams.
• Optimize data pipelines for performance, reliability, and scalability.
• Troubleshoot production data issues and ensure timely resolution.
• Follow best practices for version control, code quality, testing, and deployment.

Mandatory Skills

• Python
• ETL
• SQL
• CI/CD
• DevOps
• Git / Version Control
• Strong problem-solving and debugging skills

What you'll need

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 5+ years of professional data engineering experience.
• Experience designing and building cloud-native data solutions.
• Strong expertise with Google Cloud Platform, including BigQuery. Experience developing transformation frameworks using dbt.
• Strong SQL and Python programming skills.
• Experience with PostgreSQL or other relational databases.
• Experience orchestrating workflows using Apache Airflow or Cloud Composer.
• Experience implementing Infrastructure as Code using Terraform. Experience building CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar platforms.
• Experience developing scalable batch and streaming data pipelines. Strong problem-solving skills with the ability to balance scalability, reliability, and cloud cost optimization.

Preferred Qualifications

• Experience with Pub/Sub, Datastream, Dataflow, Cloud Storage, Cloud Functions, or Cloud Run.
• Experience building multi-tenant SaaS platforms.
• Experience implementing metadata-driven governance, lineage, and data quality frameworks.
• Experience supporting AI, machine learning, or customer-facing analytics platforms.
• Experience with Kubernetes and Docker.

About Us:

The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Job Summary:

We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.

As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.

Key Responsibilities:

• Design, develop, test, and maintain optimal data pipeline and ETL architectures.
• Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
• Prepare and optimize data for predictive and prescriptive modeling.
• Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
• Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
• Utilize big data tools and frameworks to optimize data acquisition and preparation.
• Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
• Develop and curate data models for analytics, dashboards, and reports.
• Conduct code reviews, maintain production-level code, and implement testing approaches.
• Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
• Drive innovation and implement efficient new approaches to data engineering tasks.

Must-Have Skills:

• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
• 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
• 3–5 years of experience designing and implementing data warehouse solutions.
• Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
• Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
• Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
• Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
• Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
• Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
• Strong problem-solving, communication, and collaboration skills.

Good-to-Have Skills:

• Experience in integrating ERP data into data lakes.
• Experience with traditional ETL tools (e.g., Talend, Pentaho).

Competencies:

• Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
• Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
• Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
• Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
• Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Application Details

Ready to make an impact? Apply today and become part of the QX Impact team!

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

Data Engineer Short Hiring Post

🚨 Hiring: Data Engineer

🔹 Experience: 5–9 Years

🔹 Location: Bangalore / Hyderabad

🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling

🔹 Process: L1 Virtual → L2 F2F Karat Test

🔹 F2F: Bangalore / Hyderabad Location

🔹 Positions: Immediate requirement

⚠️ Note: Candidates must be available for F2F Karat immediately after L1.

#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners

Job Description:

We are looking for an experienced Ab Initio Developer to join our team. The candidate will be responsible for developing, enhancing, and maintaining data integration and ETL solutions using Ab Initio.

Roles & Responsibilities:

• Develop and maintain ETL workflows using Ab Initio.
• Design and develop data integration solutions based on business requirements.
• Work with Ab Initio GDE, Co>Operating System, and related components.
• Develop and optimize graphs, plans, and batch processes.
• Write and optimize SQL queries for data processing.
• Perform data validation, debugging, and issue resolution.
• Analyze and improve the performance of existing ETL processes.
• Work with business and technical teams to understand requirements.
• Support production deployments and troubleshoot data-related issues.
• Follow coding, testing, and documentation standards.

Required Skills:

• 5–8 years of experience in Ab Initio Development.
• Strong experience in Ab Initio ETL/Data Integration.
• Hands-on experience with Ab Initio GDE and Co>Operating System.
• Good knowledge of SQL and database concepts.
• Experience in ETL development, debugging, and performance tuning.
• Good communication and problem-solving skills.