Data Analyst-Associate

Minimum Degree Required (BQ) *: Bachelors Degree Degree Preferred: Bachelors Degree Required Field(s) of Study (BQ): Computer Science, Information Technology, Data Analytics, Data Engineering Preferred Field(s) of Study: Cloud Computing, Software Engineering Minimum Year(s) of Experience (BQ) *: 4+ years of experience Certification(s) Preferred: Databricks Certified Data Analyst Associate Databricks Certified Data Engineer Associate AWS Certified Cloud Practitioner Microsoft Power BI Data Analyst c ertification (PL-300). Certifications are preferred, not required; hands-on experience carries more weight. Required Knowledge/Skills (BQ): Strong SQL: joins, subqueries, CTEs, window functions, aggregations, and query optimization, on SQL Server or another relational database.

Ability to build and maintain database objects such as tables, views, indexes, and stored procedures. Hands-on Databricks experience: notebooks, Spark SQL, Delta tables, and building datasets in Bronze, Silver, and Gold layers; working knowledge of PySpark. Python (pandas, PySpark) for data transformation, validation, and automation.

Working knowledge of AWS for data: Amazon S3 for storage and IAM basics, with exposure to Athena, Glue, or Redshift. Experience extracting and transforming large datasets using SQL-based processing and ETL/ELT techniques, including incremental loads. Experience developing operational reports and dashboards in Power BI or Tableau; advanced Excel including pivot tables and formulas.

Experience performing data validation, reconciliation, and troubleshooting data discrepancies. Strong understanding of data modeling and analytics dataset design (fact and dimension tables, star schemas). Ability to analyze large datasets and identify trends, patterns, and operational insights.

Awareness of HIPAA and PHI handling, and strong analytical thinking and problem-solving skills. Preferred Knowledge/Skills *: Databricks Workflows, Unity Catalog, Auto Loader, and Databricks SQL dashboards. AWS Glue (jobs and Data Catalog), Athena, Lambda, and CloudWatch.

Azure Data Factory and ADLS Gen2, since some engagements run on Azure. Experience building or supporting ETL/ELT pipelines, and migrating SQL Server logic to a lakehouse. Exposure to Alteryx, Informatica, or similar ETL tools.

Git and basic CI/CD for data code. Microsoft Power Platform (Power Apps, Power Automate) for workflow automation. Experience with healthcare datasets or Revenue Cycle Management (RCM) environments, including EDI X12 835/837.

Healthcare experience is not mandatory. QUALIFICATIONS: Education /

Experience

BE/BTECH, ME/MTECH, MBA, BCA/MCA, or a related field, or an equivalent amount of relevant professional experience. 4+ years of experience in data analytics, data engineering, or reporting roles. Hands-on experience with SQL databases and with Databricks (Spark SQL, Delta tables). Working experience with Python and with AWS data storage such as Amazon S3.

Experience building dashboards, analytics datasets, and operational reports in Power BI or Tableau. Experience with ETL pipelines or data transformation workflows. Experience working with large operational datasets, including validation and reconciliation.

Experience working in healthcare, insurance, or regulated industries is preferred. Additional Information: Shift timings: Flexible to work in night shifts (US Time zone) Experience Level: 3–5 years Mode of working: Work from office Line of Service: Advisory Designation: Associate Role: Data Analyst (Databricks, SQL & AWS)

Location

Bangalore Primary Technology Stack: SQL Server, Databricks (Spark SQL, PySpark, Delta Lake), Python, AWS (S3, IAM), Power BI, Excel Preferred Technologies: Databricks Workflows / Unity Catalog / Auto Loader, AWS Glue / Athena / Lambda, Azure Data Factory, Tableau, Alteryx / Informatica, Git, Power Automate