5+ Datawarehousing Jobs in Delhi, NCR and Gurgaon | Datawarehousing Job openings in Delhi, NCR and Gurgaon
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Responsibilities
Design and execute ETL test scenarios, test cases and test scripts based on business and technical requirements.
Validate source-to-target data mapping, transformation rules, business rules and data flows.
Perform ETL, Data Warehouse and Database Testing across multiple data sources and target systems.
Validate data extraction, transformation, loading and reconciliation processes.
Perform data validation, data completeness, data accuracy and data integrity testing.
Write complex SQL queries for backend data validation, reconciliation and defect analysis.
Validate source-to-target mappings and identify data discrepancies. Perform database testing involving joins, stored procedures, views, functions, indexes and constraints.
Test incremental loads, full loads, CDC and batch processing where applicable.
Validate ETL workflows, schedules, dependencies and error-handling mechanisms.
Perform data reconciliation between source and target systems and investigate mismatches.
Validate duplicate records, missing records, null values, data truncation and transformation errors.
Execute regression, integration, system and end-to-end testing for ETL/data pipelines.
Validate large-volume datasets and perform data quality and consistency checks.
Work with developers, data engineers, business analysts and product teams to resolve data-related issues.
Analyze ETL job failures and assist development teams with root-cause analysis (RCA). Log, track and manage defects using tools such as Jira, Azure DevOps or similar.
Prepare test execution reports, defect reports and testing status updates.
Participate in requirement analysis, test planning, estimation and defect triage meetings.
Support UAT, production validation and post-release data verification.
Ensure testing complies with enterprise data governance, security, privacy and quality standards.
Work in an Agile/Scrum environment and participate in sprint planning, daily stand-ups, reviews and retrospectives.
Collaborate with globally distributed teams and stakeholders across business and technology functions.
Understand insurance-domain data such as policy, customer, claims, billing, premium and financial data is an advantage.
Requirements
4–6 years of hands-on experience in ETL Testing / Data Warehouse Testing / Database Testing.
Strong understanding of ETL concepts, data warehousing and data integration processes.
Strong hands-on SQL skills including complex joins, subqueries, CTEs, aggregations and data reconciliation queries.
Experience with ETL tools such as Informatica, IBM DataStage, SSIS, Talend, Azure Data Factory or similar.
Experience testing large-volume data and enterprise data pipelines. Good understanding of Dimensional Data Modeling, Star Schema, Snowflake Schema, Fact and Dimension tables.
Strong knowledge of source-to-target mapping and transformation validation.
Experience with Oracle, SQL Server, DB2, PostgreSQL or other relational databases.
Knowledge of batch processing, scheduling, incremental/full loads and data migration testing.
Experience with API, web service or downstream application data validation is preferred.
Good understanding of SDLC, STLC, defect lifecycle and Agile methodologies.
Experience with Jira, Azure DevOps, ALM or similar test/defect management tools.
Exposure to cloud data platforms such as Azure/AWS is an added advantage.
Exposure to Python or scripting for test-data validation/automation is desirable.
Knowledge of data quality, reconciliation, data lineage and data governance.
Strong analytical and problem-solving skills with the ability to investigate complex data issues.
Excellent communication and stakeholder-management skills.
Prior experience in Insurance, BFSI or other regulated enterprise environments will be highly preferred.
PythonRoles & Responsibilities
- Design, develop, and deliver scalable end-to-end data pipelines using Azure Data Factory, ensuring robust integration
of enterprise-wide data from diverse sources
• Build and optimize data engineering workflows using Databricks and PySpark
• Write efficient, high-performance SQL for data transformation and analysis
• Work with the Azure Cloud platform and associated services, applying strong understanding of data warehousing,
data models, and pipelines
• Provide technical leadership to a team of developers, including code reviews and enforcing best practices across the
development lifecycle
• Oversee CI/CD implementation using Azure DevOps, managing deployments across development, QA, and production
environments with proper change control processes
• Collaborate with cross-functional teams to translate business requirements into scalable data solutions
• Ensure data quality, reliability, and performance across all pipelines and platforms
Ideal Candidate
1Strong Azure Databricks Engineer / Senior Data Engineer Profile
2Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.
3Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.
4Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.
5Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.
6Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.
7Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.
8Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.
9Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.
10Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.
Job Title : Report (Power BI) Engineer / Developer
Experience : 5+ Years
Work Mode : Remote (4 days/month office visit)
Locations : Noida, Hyderabad, Chennai, Pune, Bengaluru
Job Summary :
We are looking for an experienced Report (Power BI) Engineer / Developer to design and develop business-critical reporting solutions. The ideal candidate should have strong expertise in Power BI dashboards and paginated reports, along with hands-on experience in SQL Server, Snowflake, and Databricks.
Mandatory Skills :
Power BI, Power BI Dashboards, Paginated Reports, SQL Server, T-SQL, Snowflake, Databricks, Data Warehousing, ETL, SQL Query Optimization.
Key Skills Required :
- 5+ years of experience in Power BI development.
- Strong hands-on experience with Power BI Dashboards and Paginated Reports.
- Excellent knowledge of SQL Server and T-SQL development.
- Experience with Snowflake and Databricks.
- Understanding of data warehousing concepts, ETL processes, and SQL performance optimization.
- Strong communication and collaboration skills.
Preferred Skills :
- Experience with cloud data modernization projects.
- Knowledge of data security and compliance practices.
Note : Comprehensive background verification, including education, employment, criminal, credit, and drug screening, is mandatory.
Experience: 6-9 yrs
Location: NoidaJob Description:
- Must Have 3-4 Experience in SSIS, Mysql
- Good Experience in Tableau
- Experience in SQL Server.
- 1+ year of Experience in Tableau
- Knowledge of ETL Tool
- Knowledge of Dataware Housing
Python
Amazon Web Services (AWS)As a Data Warehouse Engineer in our team, you should have a proven ability to deliver high-quality work on time and with minimal supervision.
Develops or modifies procedures to solve complex database design problems, including performance, scalability, security and integration issues for various clients (on-site and off-site).
Design, develop, test, and support the data warehouse solution.
Adapt best practices and industry standards, ensuring top quality deliverable''s and playing an integral role in cross-functional system integration.
Design and implement formal data warehouse testing strategies and plans including unit testing, functional testing, integration testing, performance testing, and validation testing.
Evaluate all existing hardware's and software's according to required standards and ability to configure the hardware clusters as per the scale of data.
Data integration using enterprise development tool-sets (e.g. ETL, MDM, Quality, CDC, Data Masking, Quality).
Maintain and develop all logical and physical data models for enterprise data warehouse (EDW).
Contributes to the long-term vision of the enterprise data warehouse (EDW) by delivering Agile solutions.
Interact with end users/clients and translate business language into technical requirements.
Acts independently to expose and resolve problems.
Participate in data warehouse health monitoring and performance optimizations as well as quality documentation.
Job Requirements :
2+ years experience working in software development & data warehouse development for enterprise analytics.
2+ years of working with Python with major experience in Red-shift as a must and exposure to other warehousing tools.
Deep expertise in data warehousing, dimensional modeling and the ability to bring best practices with regard to data management, ETL, API integrations, and data governance.
Experience working with data retrieval and manipulation tools for various data sources like Relational (MySQL, PostgreSQL, Oracle), Cloud-based storage.
Experience with analytic and reporting tools (Tableau, Power BI, SSRS, SSAS). Experience in AWS cloud stack (S3, Glue, Red-shift, Lake Formation).
Experience in various DevOps practices helping the client to deploy and scale the systems as per requirement.
Strong verbal and written communication skills with other developers and business clients.
Knowledge of Logistics and/or Transportation Domain is a plus.
Ability to handle/ingest very huge data sets (both real-time data and batched data) in an efficient manner.
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