Andor Tech is a specialized technology staffing and consulting firm partnering with global enterprises to deliver high-impact data and analytics talent. We are currently engaged by a leading global financial data provider — a company that powers investment decisions, risk modeling, and regulatory reporting for Tier-1 banks, asset managers, and fintechs across 40+ countries. This client operates one of the world’s most comprehensive financial data lakes, ingesting petabytes of structured and unstructured market, reference, and alternative data daily.
We are hiring a Senior Business Data Analyst to join the client’s Bangalore-based analytics hub on a permanent, full-time basis. This is a Work-From-Office (WFO) role located in the Embassy TechVillage / Outer Ring Road corridor, with a expectation of 5 days on-site. The team follows a hybrid Agile cadence — two-week sprints, daily stand-ups, and quarterly PI planning — but the culture emphasizes deep work blocks and asynchronous documentation over meetings.
As a Business Data Analyst, you will sit at the intersection of data engineering, product analytics, and business strategy. Your primary mandate: translate complex financial data questions into reliable, scalable analytical assets that drive product decisions, client reporting, and regulatory submissions. You will own the full lifecycle — from requirement gathering with product managers and quant researchers, through data discovery and profiling in Snowflake and Redshift, to building governed data marts, dashboards, and self-service tools used by 200+ internal stakeholders.
Key responsibilities:
1. Design and maintain dimensional data models (star/snowflake schemas) for equities, fixed income, and derivatives reference data, ensuring conformance to FIBO and ISO 20022 standards.
2. Write and optimize complex SQL (CTEs, window functions, lateral joins) for daily ETL/ELT pipelines orchestrated via Apache Airflow and dbt, targeting sub-30-minute SLA for 500+ million row refreshes.
3. Develop Python-based data quality frameworks using Great Expectations and pandas, implementing automated row-level, column-level, and referential integrity checks with Slack/PagerDuty alerting.
4. Build and govern Tableau and Power BI dashboards for client-facing reporting (fact sheets, performance attribution, ESG scores), enforcing row-level security and certified data source policies.
5. Partner with quant research teams to prototype alternative data signals (satellite imagery, NLP on earnings calls, supply chain graphs) using JupyterLab and MLflow, then productionize viable features into the feature store (Feast).
6. Lead data discovery workshops with business stakeholders, documenting lineage in Alation and maintaining a living data dictionary with business glossary mappings.
7. Conduct root-cause analysis on data discrepancies reported by clients — tracing from source vendor feeds (Refinitiv, Bloomberg, FactSet) through normalization layers to delivery endpoints.
8. Mentor 2–3 junior analysts on SQL best practices, version control (Git/GitLab), and documentation standards; conduct code reviews for all dbt model merges.
9. Collaborate with data engineering on schema evolution strategies — backward-compatible migrations, deprecation policies, and contract testing using dbt contracts.
10. Contribute to the analytics chapter’s knowledge base: write runbooks, create reusable macro libraries, and present at monthly ‘Data Demo Days’.
Work environment & culture:
The Bangalore analytics hub comprises 45 professionals — data engineers, analysts, ML engineers, and product managers — reporting into a Singapore-based Chief Data Officer. The team values technical rigor over hierarchy; decisions are made via RFCs (Request for Comments) in Confluence. You’ll have a dedicated learning budget (₹1.5L/year) for conferences (Strata, PyData), certifications (SnowPro, dbt), or courses. Hackathons run quarterly; last edition produced a prototype for automated ESG controversy detection using LlamaIndex.
Candidate requirements:
- 6+ years of hands-on experience in business data analysis, preferably in financial services, capital markets, or fintech.
- Expert-level SQL: comfortable with query plan analysis (EXPLAIN ANALYZE), partitioning strategies, and time-series analytics.
- Production-grade Python: pandas, NumPy, SQLAlchemy, pytest, logging, type hints (mypy), and packaging (poetry).
- Proven track record building governed analytics products — not just ad-hoc queries — using dbt, Airflow, and BI tools at scale.
- Strong grasp of financial instruments: corporate actions, yield curves, OTC derivatives pricing, and regulatory frameworks (MiFID II, SFDR, BCBS 239).
- Experience with cloud data platforms: Snowflake (preferred), Redshift, or BigQuery; familiarity with IAM, RBAC, and cost optimization.
- Excellent communication: ability to explain technical trade-offs to non-technical product owners and write clear decision logs.
- Bachelor’s or Master’s in Computer Science, Statistics, Mathematics, Engineering, or Quantitative Finance.
Technical stack (real tools in use):
Snowflake, Redshift, dbt Core, Apache Airflow, Python 3.11+, pandas, Great Expectations, Tableau Server, Power BI, GitLab CI/CD, JupyterLab, MLflow, Feast, Alation, Confluence, Slack, PagerDuty, AWS (S3, Lambda, Step Functions), Docker.
Benefits & compensation context:
Base salary: ₹35–48 LPA (commensurate with experience), plus 15–20% annual performance bonus. Comprehensive health insurance (family floater, ₹15L cover), term life, and OPD. 25 days annual leave + 10 company holidays + 5 wellness days. NPS-linked referral bonus (₹1L per senior hire). Relocation support up to ₹3L if moving from outside Bangalore. Equipment: MacBook Pro M3 or Dell XPS 15 + dual 27" 4K monitors. Udemy Business + Coursera Plus enterprise access.
Career growth opportunities:
Clear dual-track progression: Senior Business Data Analyst → Lead Analyst → Principal Analyst (IC track) or → Analytics Engineering Manager → Director of Data Products (management track). High performers get exposure to global strategy offsites in London/NY and can lead cross-region initiatives (e.g., APAC data mesh rollout). The client promotes internally — 60% of leadership roles filled from within analytics.
Hiring process & timeline:
1. Initial screen (30 min) with Andor Tech recruiter — verify notice period, WFO readiness, and core SQL/Python depth.
2. Technical assessment (take-home, 90 min): real-world data modeling + SQL optimization + Python data quality task using a sanitized financial dataset.
3. Panel interview (60 min) with two senior analysts and a data engineer — deep dive on past projects, system design, and stakeholder management.
4. Client hiring manager interview (45 min) — focus on domain knowledge, communication, and cultural alignment.
5. Offer rollout within 3 business days of final interview. Target onboarding: 15–20 days from offer acceptance. Immediate joiners (notice ≤ 20 days) strongly preferred.
If your background matches and you’re ready for a high-autonomy, high-impact role shaping how global finance consumes data, send your updated CV (PDF) to
[email protected] with subject: "Sr Business Data Analyst | Bangalore | [Your Notice Period]". Include a 3–4 bullet summary of your most relevant financial data project.