Urgent! Senior Data Analyst - Python/Tableau Job Opening In Chandigarh – Now Hiring Confidential
<p><p><b>Role : Senior Analytics Engineer (Customer Success)</b><br/><br/>- Shift : 4 PM - 12 AM (Overlap with USA - Eastern Time)<br/><br/>- Experience : 5 - 6 years (startup background strongly preferred)<br/><br/>- Focus mix : Data Analytics 50%, Data Engineering 30%, Customer Success 20%</p><br/><p><b>Company Overview :</b></p><p><br/></p><p>We are a unified, financial-services CRM with an AI agent co-pilot that connects fragmented data, automates workflows, and powers outcome-driven customer journeys - end-to-end from lead to funding, especially in lending.
The platform is expanding across broader financial-services use cases beyond mortgage.</p><br/><p><b>Role Purpose :</b></p><p><br/></p><p>Our customers (banks, NBFCs, lenders, fintechs) want trustworthy, decision-grade data and clear insights embedded in CRM workflows.
Youll be the hands-on owner who models the data, builds scalable pipelines, ships crisp BI, and partners with customer teams to drive measurable business outcomes (conversion, funding velocity, retention/upsell, agent productivity).</p><br/><p><b>Key Responsibilities :</b></p><p><b><br/></b></p><p><b>Data Analytics - 50% : </b></p><p><br/></p><p>- Translate customer goals into analytical frameworks, certified datasets, and BI assets (Power BI/Tableau/Metabase) with semantic layers and documentation.<br/><br/>- Build cohorts, funnels, lifetime value and propensity analyses; run A/B experiments and readouts; turn findings into actions inside CRM workflows.<br/><br/>- Define source of truth metrics (lead?app?approval?funding, NCA/roll rates overlays, agent productivity) and set up robust monitoring.</p><br/><p><b>Data Engineering - 30% :</b></p><p><br/></p><p>- Design/operate lakehouse stacks on AWS (S3 + Glue Catalog + Apache Iceberg) feeding Redshift/Postgres; build ELT/ETL in PySpark/Python.<br/><br/>- Optimize models for cost and performance; implement data contracts, tests, lineage, and CI/CD for data.<br/><br/>- Build reliable ingestion from product/CRM events and financial-services systems (e.g., loan origination, servicing, core-banking, bureau, KYC).<br/><br/>- Publish curated, self-serve datasets that power BI and CRM/AI-agent actions.</p><br/><p><b>Customer Success - 20% : </b></p><p><br/></p><p>- Lead analytical onboarding : KPI design, data readiness, success plans, enablement/training.<br/><br/>- Run QBRs with quantified impact; prioritize roadmap asks by value; turn recurring insights into playbooks inside Company<br/><br/>- Advise on compliant data usage and controls in regulated environments.</p><br/><p><b>Technology Stack : </b></p><p><br/></p><p>- Cloud/Data : AWS, S3, Glue Catalog, Apache Iceberg, Redshift, Postgres, PySpark, Python<br/><br/>- Analytics/BI : SQL (expert), Python (pandas/NumPy), Power BI/Tableau/Metabase<br/><br/>- Nice to have : dbt, Airflow/Step Functions, Terraform, GitHub Actions, event streaming (Kinesis/Kafka), reverse ETL</p><br/><p><b>Qualifications : </b></p><p><br/></p><p>- 5-6 years across analytics + data engineering, ideally in startup or high-ownership environments.<br/><br/>- Fluency in SQL and dimensional/data-vault modeling; you turn messy multi-source data into clean, documented, high-trust datasets.<br/><br/>- Hands-on lakehouse experience (Iceberg on Glue), plus Redshift/Postgres performance tuning.<br/><br/>- Analytical storytelling : you connect metric movements to operational levers and ship changes that move the funnel.<br/><br/>- Domain comfort with financial-services data (PII handling, consent, encryption, data residency; familiarity with SOC 2/GDPR/PCI principles).<br/><br/>- Customer-facing strength : translate technical detail into business impact; handle exec and ops stakeholders with ease.</p><br/><p><b>Good to have : </b></p><p><br/></p><p>- Experience instrumenting product/CRM events and mapping to lending life-cycle stages.<br/><br/>- Exposure to AI/agent-driven workflows (prompted actions, guardrails, evaluation).<br/><br/>- Building cost-aware data stacks and usage-based BI governance at scale.</p><br/></p> (ref:hirist.tech)
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Unlock Your Senior Data Potential: Insight & Career Growth Guide
Real-time Senior Data Jobs Trends in Chandigarh, India (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Senior Data in Chandigarh, India using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 474364 jobs in India and 284 jobs in Chandigarh. This comprehensive analysis highlights market share and opportunities for professionals in Senior Data roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Confidential is currently hiring and seeking a Senior Data Analyst Python/Tableau to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Confidential adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Senior Data Analyst Python/Tableau Jobs India varies, but the pay scale is rated "Standard" in Chandigarh. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Senior Data Analyst Python/Tableau typically include Mathematical Science Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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