Analytics Engineer / Data Analyst – Azure Synapse & Data Platform

Analytics Engineer / Data Analyst – Azure Synapse & Data Platform

Claidroid Technologies Pvt. Ltd. Location: Thiruvananthapuram, Kerala / Pune, Maharashtra

Work Mode: Hybrid

Experience: 5–8+ years

Engagement: Full-time opportunity

Claidroid Technologies Pvt. Ltd. is hiring an experienced

Analytics Engineer / Data Analyst – Azure Synapse & Data Platform to join an existing

enterprise data platform team . At Claidroid Technologies, our name is derived from

Cloud, AI, and Automation — the three pillars that define our innovation-driven approach to

digital transformation . Claidroid Technologies is a global digital transformation and technology services partner built by IT professionals with over three decades of industry experience, with a presence across India, Europe, and the USA. We help enterprises modernize platforms, improve operational efficiency, strengthen governance, and accelerate business outcomes. We work with leading enterprises in regulated industries, delivering scalable, high-quality technology solutions with a strong focus on

governance, quality assurance, and business alignment .

Role Overview As an

Analytics Engineer / Data Analyst , you will join an existing enterprise data platform team and play a key role in

validating, analysing, and improving data products across the platform. This is

not a traditional reporting analyst role . We are looking for someone who is equally comfortable writing

complex SQL , understanding

data architecture , tracing

data lineage , and identifying

data gaps, inconsistencies, and quality issues . You will act as a critical bridge between

engineering teams and business stakeholders , helping validate what the platform produces and surfacing what is missing, incorrect, or inconsistent. The role requires strong

technical analysis skills, curiosity, persistence , and the ability to work with

complex, undocumented, or legacy datasets in an enterprise-scale environment.

Key Responsibilities

• Interrogate foundational and use-case data products 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 , understanding where data originates, how it is transformed, and what reaches the consumption layer.

• Identify

data gaps, anomalies, unexpected transformations, and discrepancies between source systems and downstream data products.

• Validate

business logic embedded in transformation layers by comparing expected versus actual outputs across datasets.

• Reverse-engineer

data transformations by reading query outputs and comparing results across platform layers.

• Read and interpret

pipeline logic to understand what the pipeline is doing and whether the output is correct.

• Document findings clearly through structured

gap analyses, data quality assessments, data dictionaries, and investigation notes .

• Work closely with senior data engineers and solution architects to provide ground-level data evidence for

re-engineering and migration decisions .

• 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 it against platform outputs.
• Translate

business questions into well-structured

analytical data models .

• Contribute to

semantic views, analytical datasets, and self-serve reporting assets where required.

Key Requirements

• 5–8+ years of experience in a data analyst, analytics engineering, or BI engineering role with a strong technical focus.
• Expert-level SQL , including multi-table joins, window functions, aggregations, CTEs, and recursive logic.
• Strong ability to profile and explore

unfamiliar datasets without prior documentation .

• Experience querying

large-scale data platforms , including partitioned tables, Delta tables, and distributed query engines.

• Experience with

Azure Synapse SQL Pool and/or

Synapse Serverless SQL .

• Solid understanding of

medallion / lakehouse architecture , including

Raw, Harmonized, Conformed, and Consumption layers.

• Familiarity with data modelling concepts such as

surrogate keys, slowly changing dimensions, denormalization, and conformed dimensions .

• Understanding of

CDC and SCD patterns and their impact on historical data.

• Experience working with

Azure Data Lake Storage Gen2 and

Delta Lake format, including

Parquet and Delta tables .

• Familiarity with

Azure Synapse Analytics environments, including SQL Pools, Spark outputs, and storage layers.

• Experience building or contributing to

semantic layers, data models, or analytical datasets consumed by BI tools.

• Experience with

Power BI or equivalent BI tools, with an understanding of how semantic models consume underlying data products.

• Strong analytical mindset with the ability to form hypotheses about data issues and design

SQL-based tests to validate them.

• Experience with

data profiling , including null rates, cardinality checks, referential integrity checks, and distribution analysis.

• Ability to compare datasets across systems or layers and surface

meaningful discrepancies .

• Familiarity with

data quality frameworks and

rule-based validation approaches .

• Strong documentation skills, with the ability to produce clear

gap analyses, data dictionaries, and investigation findings that non-technical stakeholders can understand.

• Comfortable operating in

ambiguity , with curiosity and persistence when data does not behave as expected.

• Collaborative and inquisitive, with the ability to work within an engineering team while engaging directly with business users.
• Detail-oriented without losing sight of the bigger picture.

Preferred Skills

• Exposure to

Python, Pandas, or PySpark for data exploration beyond SQL.

• Familiarity with

dbt or similar analytics engineering frameworks.

• Experience with

dbt for analytics engineering and data model documentation .

• Familiarity with

Azure Purview or

Unity Catalog for data cataloguing and lineage.

• Exposure to

data observability or monitoring tooling .

• Background in

financial services or insurance data , including policy, sales, or CRM data structures.

• Experience working in

regulated or enterprise-scale environments .

Additional Preferences

• Candidates willing to work from

Thiruvananthapuram or Pune in hybrid mode will be preferred.

• Candidates with strong

technical analysis, SQL, data validation, and business-facing communication skills will be preferred.

• Immediate joiners or candidates serving a

short notice period will be preferred. This is an excellent opportunity to work on

enterprise-scale data platform initiatives and grow your career with a globally expanding organization.