Data Analyst

SG Analytics; Pune District; Hybrid; INR 1,200,000 - 2,200,000; Full time

Job summary

SG Analytics is seeking an experienced data analytics professional in Pune to drive data quality, lineage, and semantic modeling across large-scale data platforms. You will craft complex SQL queries, profile datasets, and validate transformations end-to-end to support BI-ready analytics & governance.

You will collaborate with senior engineers and architects to guide migration decisions and ensure data correctness across Raw, Harmonized, and Conformed layers.

Qualifications

• Expertise in SQL and data querying across large-scale platforms.
• Experience with Azure Synapse SQL Pools or Synapse Serverless SQL.
• Understanding of medallion/lakehouse architecture and data modeling.
• Ability to profile data, assess quality, and document gaps clearly.
• Familiarity with data Lake Gen2/Delta Lake formats and data governance concepts.
• Experience with BI tools (Power BI) and analytics engineering concepts.
• Knowledge of dbt or similar analytics frameworks is a plus.

Responsibilities

• Interrogate data products across the platform to assess completeness and correctness.
• Write complex SQL queries to profile and validate data end-to-end.
• Trace data lineage and understand source-to-consumption transformations.
• Identify data gaps and discrepancies; document findings for engineers and stakeholders.
• Collaborate with senior data engineers and solution architect on migrations.
• Validate business logic in transformation layers by comparing outputs.
• Support data governance via profiling and data quality rule definitions.
• Engage with business users to align data expectations with platform delivery.
• Contribute to semantic views, analytical datasets, and BI-ready assets.

Skills

Expert SQL

Azure Synapse SQL Pools

Medallion Architecture

Data Lineage

Data Profiling

Data Quality

Gap Analysis

Data Lake Storage

Delta Lake

Data Modeling

Power BI

Tools

dbt

Azure Purview

Unity Catalog

Job description

Mandatory Skills :

Expert SQL, Azure Synapse SQL Pools, Medallion Architecture, Data Lineage, Data Profiling, Data Quality & Gap Analysis, Data Lake Storage (ADLS Gen2/Delta Lake), Data Modeling, Power BI

Key Responsibilities

• Interrogate foundational and use case data products across the platform to assess completeness, correctness, and consistency
• Write complex SQL queries to explore, profile, and validate data across multiple layers from raw ingestion through to conformed and consumption datasets
• Trace data lineage end-to-end: understand where data originates, how it is transformed at each layer, and what reaches the consumption layer
• Identify data gaps, anomalies, unexpected transformations, and discrepancies between source systems and downstream data products
• Document findings clearly translating technical observations into structured gap analyses and data quality assessments that both engineers and business stakeholders can act on
• Work closely with senior data engineers and the solution architect to provide ground-level data evidence that informs re-engineering and migration decisions
• Validate business logic embedded in transformation layers by comparing expected versus actual outputs across datasets
• Support data governance efforts by profiling datasets, cataloguing findings, and contributing to data quality rule definitions
• Collaborate with business and analytics stakeholders to understand expected data behaviour and reconcile against what the platform currently delivers
• Contribute to the development of semantic views, analytical datasets, and self- serve reporting assets where required Interna

Core Technical Skills

SQL & Data Querying

• Expert-level SQL able to write complex analytical queries involving multi-tablejoins, window functions, aggregations, CTEs, and recursive logic
• Strong ability to profile and explore unfamiliar datasets without prior

documentation

• Experience querying large-scale data platforms comfortable working with partitioned tables, Delta tables, and distributed query engines
• Experience with Azure Synapse SQL Pool and/or Synapse Serverless SQL
• Ability to reverse-engineer data transformations by reading query outputs and comparing across layers

Data Platform & Architecture Literacy

• Solid understanding of medallion / lakehouse architecture (Raw / Harmonized / Conformed / Consumption) able to navigate a multi-layer platform and understand the purpose and content of each layer
• Familiarity with data modelling concepts: surrogate keys, slowly changing dimensions, denormalization, conformed dimensions
• Understanding of CDC and SCD patterns and their impact on historical data
• Ability to read and interpret data pipeline logic not necessarily build it, but understand what a pipeline is doing and whether the output is correct
• Experience working with Azure Data Lake Storage Gen2 and Delta Lake format (Parquet, Delta tables)
• Familiarity with Azure Synapse Analytics environment — navigating SQL Pools Spark outputs, and storage layers

Analytics Engineering

• Experience building or contributing to semantic layers, data models, or analytical datasets consumed by BI tools
• Familiarity with dbt or similar analytics engineering frameworks is a plus
• Ability to translate business questions into well-structured analytical data models
• Experience with Power BI or equivalent BI tools — understanding of how semantic models consume underlying data products

Data Quality & Investigation Interna

• Strong analytical mindset — able to form hypotheses about data issues, design

SQL-based tests to validate them, and clearly document conclusions

• Experience with data profiling: null rates, cardinality, referential integrity checks, distribution analysis
• Ability to compare datasets across systems or layers and surface meaningful discrepancies
• Familiarity with data quality frameworks and rule-based validation approaches

Nice to Have

• Exposure to Python (Pandas / PySpark) for data exploration beyond SQL
• Familiarity with Azure Purview or Unity Catalog for data cataloguing and lineage
• Experience with dbt for analytics engineering and data model documentation
• Exposure to data observability or monitoring tooling
• Background in financial services or insurance data (policy, sales, CRM data structures)

Experience & Profile

• 5-8+ years of experience in a data analyst, analytics engineering, or BI engineering role with a strong technical focus
• Demonstrated ability to work directly with complex, undocumented, or legacy datasets and make sense of them independently
• Comfortable operating in ambiguity — this role requires curiosity and persistence when the data does not behave as expected
• Strong documentation skills — able to produce clear gap analyses, data dictionaries, and investigation findings that non-technical stakeholders can understand
• Collaborative and inquisitive — works well embedded within an engineering team while also engaging directly with business users
• Detail-oriented without losing sight of the bigger picture — able to flag granular data issues in the context of platform-level quality and completeness
• Experience working in regulated or enterprise-scale environments (financial services a plus)