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Hiring for Data Analyst

Exp : 5 - 7 yrs

Edu : BE/B.Tech

Work Location : Noida WFO

Skills :

Expertise in SQL Server, including database design, performance tuning, query optimization, and security.

Hands-on experience developing ETL solutions using SSIS, Azure Data Factory (ADF), and Python.

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.

Job Title: Data Engineer

Job Summary: As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary for data collection, storage, processing, and analysis. You will work closely with data scientists and analysts to ensure that data is available, accessible, and in a format that can be easily consumed for business insights.

Responsibilities:

• Design, build, and maintain data pipelines to collect, store, and process data from various sources.
• Create and manage data warehousing and data lake solutions.
• Develop and maintain data processing and data integration tools.
• Collaborate with data scientists and analysts to design and implement data models and algorithms for data analysis.
• Optimize and scale existing data infrastructure to ensure it meets the needs of the business.
• Ensure data quality and integrity across all data sources.
• Develop and implement best practices for data governance, security, and privacy.
• Monitor data pipeline performance / Errors and troubleshoot issues as needed.
• Stay up-to-date with emerging data technologies and best practices.

Requirements:

Bachelor's degree in Computer Science, Information Systems, or a related field.

Experience with ETL tools like Matillion,SSIS,Informatica

Experience with SQL and relational databases such as SQL server, MySQL, PostgreSQL, or Oracle.

Experience in writing complex SQL queries

Strong programming skills in languages such as Python, Java, or Scala.

Experience with data modeling, data warehousing, and data integration.

Strong problem-solving skills and ability to work independently.

Excellent communication and collaboration skills.

Familiarity with big data technologies such as Hadoop, Spark, or Kafka.

Familiarity with data warehouse/Data lake technologies like Snowflake or Databricks

Familiarity with cloud computing platforms such as AWS, Azure, or GCP.

Familiarity with Reporting tools

Teamwork/ growth contribution

• Helping the team in taking the Interviews and identifying right candidates
• Adhering to timelines
• Intime status communication and upfront communication of any risks
• Tech, train, share knowledge with peers.
• Good Communication skills
• Proven abilities to take initiative and be innovative
• Analytical mind with a problem-solving aptitude

Good to have :

Master's degree in Computer Science, Information Systems, or a related field.

Experience with NoSQL databases such as MongoDB or Cassandra.

Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.

Knowledge of machine learning and statistical modeling techniques.

If you are passionate about data and want to work with a dynamic team of data scientists and analysts, we encourage you to apply for this position.

• Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
• Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
• Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
• Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
• Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
• Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree  and Random forest Algorithms.
• PolyBase queries for exporting and importing data into Azure Data Lake.
• Building data models both tabular and multidimensional using SQL Server data tools.
• Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
• Programming experience using python libraries NumPy, Pandas and Matplotlib.
• Implementing NOSQL databases and writing queries using cypher.
• Designing end user visualizations using Power BI, QlikView and Tableau.
• Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
• Experience using the expression languages MDX and DAX.
• Experience in migrating on-premise SQL server database to Microsoft Azure.
• Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
• Performance tuning complex SQL queries, hands on experience using SQL Extended events.
• Data modeling using Power BI for Adhoc reporting.
• Raw data load automation using T-SQL and SSIS
• Expert in migrating existing on-premise database to SQL Azure.
• Experience in using U-SQL for Azure Data Lake Analytics.
• Hands on experience in generating SSRS reports using MDX.
• Experience in designing predictive models using Python and SQL Server.
• Developing machine learning models using Azure Databricks and SQL Server