SQL Data Analyst

Sutherland Global Service Limited; Bengaluru; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

Sutherland Global Service Limited in Bengaluru is seeking a Senior Data Analyst to dive deep into data, answer business questions with self-written SQL, and ensure data quality across Azure-based platforms. This hands-on role focuses on data profiling, validation, and uncovering insights that power customer-facing applications.

You'll collaborate with data engineering, product, and business teams, connect to data sources, and document findings to communicate complex data stories clearly to

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Statistics, Mathematics, Business, or a related field.
• Master’s degree in Information Systems, Computer Science, Data Analytics, or Business Administration is an asset.
• Excellent analytical and problem‑solving skills, with a track record of drawing conclusions from data, spotting patterns, and getting to root causes.
• Genuine curiosity: you investigate beyond the obvious answer, ask good questions, and keep digging until the data makes sense.
• Comfortable working with ambiguous or incomplete requirements and turning loosely defined business questions into a clear analytical approach.
• Ability to understand business requirements and determine what is actually happening in the underlying data.
• Ability to make sense of complex, unfamiliar datasets with strong attention to detail.
• Clear communicator who can explain data findings, gaps, and risks to business partners in plain language.
• Self‑driven and able to contribute quickly with minimal ramp‑up, working both independently and collaboratively within a team.
• Experience in the life science or biotechnology industry is a plus.

Responsibilities

• Partnering with business stakeholders to understand their questions and requirements, asking the clarifying questions needed to uncover the underlying business need, especially when requests are ambiguous or incomplete.
• Independently connecting to data sources and writing SQL to explore, profile, and understand unfamiliar datasets and data structures.
• Joining and analyzing data across multiple tables and sources to understand the relationships between datasets and how data connects end to end.
• Identifying missing records, data gaps, inconsistencies, and data quality issues, then investigating root causes and recommending resolutions.
• Performing exploratory and ad‑hoc analysis to uncover trends, patterns, and anomalies, and using data to validate (or challenge) business assumptions.
• Gathering and analyzing data requirements to support the ingestion of new data sources into the platform, and tracing and validating data as it moves from Azure Data Lake through Databricks to the SQL layer.
• Performing data validation and testing to ensure data is complete, accurate, and fit for use by the business and by customer‑facing applications.
• Documenting findings, data mappings, and business rules, and communicating results clearly to both technical and non‑technical audiences.
• Working cross‑functionally with data engineering, product, and business teams to ensure alignment and successful delivery.

Skills

SQL

Data profiling

Data mining

Data validation

Data quality

Joins

Education

Bachelor's degree

Master's degree asset

Tools

Databricks

Azure Data Lake Storage

Python

Job description

Job Description

As a Senior Data Analyst, you’ll be the person on our Enterprise Data and Analytics team who finds out what the data is really saying. Business stakeholders will bring you questions that are often loosely defined. Your job is to clarify what they actually need, connect directly to the underlying data, and use SQL to explore, profile, and investigate it until you can give a clear, evidence-based answer. You’ll uncover trends, anomalies, gaps, and data quality issues across our Azure-based data platform (Azure Data Lake, Databricks, and SQL), and help bring new data into the platform that powers our customer-facing applications. This is a hands‑on, technical analysis role for someone who is naturally curious and enjoys being a data “sleuth.”

Is this role right for you?

This is a hands‑on data investigation role, not a reporting, dashboard, or traditional business analysis position. Our data is delivered to customers through APIs and applications rather than BI dashboards, so the work centers on querying, profiling, and understanding data, not building visualizations or focusing primarily on requirements documentation. If you enjoy writing your own SQL to get to the bottom of a question, you’ll thrive here.

Our team thrives on curiosity, collaboration, and a commitment to excellence. We work closely with data engineering, product, and business partners to deliver trusted, high‑quality data that shapes the future of research and development.

In this role, primary responsibilities include:

• Partnering with business stakeholders to understand their questions and requirements, asking the clarifying questions needed to uncover the underlying business need, especially when requests are ambiguous or incomplete.
• Independently connecting to data sources and writing SQL to explore, profile, and understand unfamiliar datasets and data structures.
• Joining and analyzing data across multiple tables and sources to understand the relationships between datasets and how data connects end to end.
• Identifying missing records, data gaps, inconsistencies, and data quality issues, then investigating root causes and recommending resolutions.
• Performing exploratory and ad‑hoc analysis to uncover trends, patterns, and anomalies, and using data to validate (or challenge) business assumptions.
• Gathering and analyzing data requirements to support the ingestion of new data sources into the platform, and tracing and validating data as it moves from Azure Data Lake through Databricks to the SQL layer.
• Performing data validation and testing to ensure data is complete, accurate, and fit for use by the business and by customer‑facing applications.
• Documenting findings, data mappings, and business rules, and communicating results clearly to both technical and non‑technical audiences.
• Working cross‑functionally with data engineering, product, and business teams to ensure alignment and successful delivery.

Qualifications

We are looking for the following minimum qualifications for this role:

• Bachelor’s degree in Computer Science, Information Systems, Statistics, Mathematics, Business, or a related field.
• Master’s degree in Information Systems, Computer Science, Data Analytics, or Business Administration is an asset.
• Excellent analytical and problem‑solving skills, with a track record of drawing conclusions from data, spotting patterns, and getting to root causes.
• Genuine curiosity: you investigate beyond the obvious answer, ask good questions, and keep digging until the data makes sense.
• Comfortable working with ambiguous or incomplete requirements and turning loosely defined business questions into a clear analytical approach.
• Ability to understand business requirements and determine what is actually happening in the underlying data.
• Ability to make sense of complex, unfamiliar datasets with strong attention to detail.
• Clear communicator who can explain data findings, gaps, and risks to business partners in plain language.
• Self‑driven and able to contribute quickly with minimal ramp‑up, working both independently and collaboratively within a team.
• Experience in the life science or biotechnology industry is a plus.

Technical Expertise required:

• Minimum of 5 years’ hands‑on SQL experience in a data analysis role, writing your own queries to explore and investigate data (not only running predefined reports or executing predefined ETL mappings).
• Strong proficiency with multi‑table joins (inner and outer), aggregations, and queries that surface missing or unmatched records, duplicates, and anomalies.
• Minimum of 5 years’ experience in data profiling, data mining, and data validation/testing.
• Proven experience analyzing relationships between datasets and investigating data quality issues across multiple sources or systems.
• Experience supporting data ingestion, integration, or migration initiatives, including source‑to‑target analysis and data mapping.

Nice to have:

• Experience querying data in Databricks (Spark SQL / notebooks).
• Familiarity with Microsoft Azure data services, especially Azure Data Lake Storage, and layered (bronze/silver/gold) data architectures.
• Basic Python for data exploration and analysis.
• Experience working on data products delivered through APIs or applications.
• Experience working in an Agile delivery environment.