{"id":3609897,"url":"https://alion.io/job/falcon-data-analyst","title":"Data Analyst","company":{"id":2123061,"name":"Falcon","domain":"falconfs.com","url":"https://alion.io/company/falconfs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"D","score":50,"open_postings":12,"ghost_share":0.833,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":400000,"max":500000,"currency":"INR","period":"year","gross":null,"usd_annual":5291},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Matplotlib","optional":false},{"name":"NumPy","optional":false},{"name":"Plotly","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Seaborn","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Amazon S3","optional":true},{"name":"AWS","optional":true},{"name":"AWS Lambda","optional":true},{"name":"ETL/ELT","optional":true}],"status":"live","first_seen_at":"2026-11-02T13:07:03Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-04T13:10:16Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":1},"description":"Job Description | Data Analyst\nWho are we?\nWe are a fast-growing AI-first fintech platform enabling banks, NBFCs, and financial institutions to launch and scale next-generation credit products, including credit cards, credit lines, lending, and payment solutions. Our platforms process high-volume financial transactions and power business-critical customer journeys where reliability, performance, and security are non-negotiable.\nWe are looking for a Data Analyst who thrives in high-ownership environments, enjoys solving complex engineering challenges, and is passionate about building products that directly impact millions of users and financial institutions.\n For more details, please visit https://falconfs.com/\nJob Summary:\nWe are looking for a Data Analyst with strong SQL, Python, Excel, and data visualization skills to support banking reports, credit card analytics, data reconciliation, and reporting. The candidate will analyse large datasets, ensure data accuracy, and build dashboards to support business decisions.\nKey Responsibilities:\nWrite and optimize SQL queries to extract, transform, and analyse large datasets.\nUse Python (pandas, NumPy) to clean, transform, and analyse data, and to build scripts for reconciliation and data validation.\nPrepare and validate banking, credit card, and regulatory reports.\nIdentify data discrepancies, investigate root causes, and implement data quality checks.\nBuild and maintain dashboards using Amazon Quick Sight, Tableau, or Power BI.\nCreate ad hoc analyses and visualizations using Python libraries such as Matplotlib, Seaborn, or Plotly.\nUse Excel for data analysis, reconciliation, and reporting.\nSupport automation of recurring reports and data processing workflows using Python.\nCollaborate with technical and business teams to clarify requirements and deliver reports on time.\nDocument reporting logic, business rules, and validation procedures.\nRequired Skills & Qualifications:\nBachelor’s degree in a relevant field.\n2+ years of experience in data analytics, MIS reporting, or business intelligence.\nStrong SQL skills, including joins, CTEs, aggregations, and window functions.\nGood proficiency in Excel, including lookup functions, pivot tables, and data reconciliation.\nHands-on Python scripting for data analysis and automation, including pandas and NumPy.\nExperience with Python visualization libraries such as Matplotlib, Seaborn, or Plotly.\nHands-on experience with a data visualization tool: Amazon Quick Sight, Tableau, or Power BI.\nStrong analytical thinking, attention to detail, and problem-solving skills.\nGood to Have:\nExposure to AWS Athena, S3, and Lambda.\nUnderstanding of data quality checks, ETL processes, and 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