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Senior Data Analyst
Not a reporting-only role. We're looking for someone who can take an ambiguous business question, trace it through the enterprise data landscape, and come back with a documented data model, a field-level mapping, and a validated answer.
If you enjoy sitting between business stakeholders, data architects, data engineers and BI developers - and speaking all four languages fluently - this one is for you.
The role at a glance
- Experience: 7–10 years in Data Analysis, Business Analysis or Data Management
- Location: Hybrid – India
- Engagement: Full-Time
- Domain: Data Analytics | Data Modelling | Business Intelligence
What you'll actually do
- Translate business processes and reporting needs into technical data requirements
- Develop conceptual, logical and physical data models; create and maintain ERDs
- Author source-to-target mappings, transformation rules and data lineage documentation
- Own end-to-end data flow documentation, from source systems through to the BI layer
- Lead validation and reconciliation — define test cases, execute UAT, sign off on data quality
- Identify data gaps, inconsistencies and improvement opportunities, and drive them to closure
- Define KPIs and metric logic, and validate published dashboards against source data
- Work in Scrum — write user stories, participate in ceremonies, own sprint deliverables
What we're looking for
- Advanced SQL: complex joins, CTEs, window and analytic functions (ROW_NUMBER, RANK, LAG/LEAD), aggregations, stored procedures, and genuine query optimisation — execution plans, indexing, partition pruning
- Data modelling: normalisation and deliberate denormalisation, star and snowflake schemas, fact vs dimension design, grain definition, conformed dimensions, Slowly Changing Dimensions (Type 1/2/3), surrogate keys
- Enterprise data architecture: layered designs (raw → staging → curated → semantic), awareness of Kimball, Inmon, Data Vault or medallion approaches, OLTP vs OLAP
- Exploratory data analysis: profiling, data quality assessment, outlier and duplicate detection, data preparation at volume
- Data quality and governance: completeness, accuracy, consistency, timeliness, uniqueness, validity — plus reconciliation techniques like control totals and referential integrity checks
- Delivery: Agile/Scrum, JIRA and Confluence, clear written specifications, and strong stakeholder communication
Nice to have
Snowflake, Microsoft Azure (Synapse, ADLS Gen2), Databricks, BigQuery or Redshift; dbt, Azure Data Factory or Informatica; Power BI, Tableau or Looker (DAX/LOD a plus); Python for validation and reconciliation scripting; exposure to SAP or Oracle ERP data; relevant certifications.
Why Techylla
We're an IT and Consulting organisation operating across the US and India, built on four values we actually use: Relationship, Commitment, Integrity and Collaboration. You'll get competitive compensation, comprehensive medical cover, a hybrid model, and genuine room to grow through knowledge sharing and mentoring.
Click on Apply to know more.