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About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As a Senior Data Engineer , you will own the data foundation of Zinnov’s GCC Intelligence Platform—building reliable multi-tenant pipelines and KPI-ready datasets across Finance and Hiring domains. Your work enables downstream dashboards and AI agents to operate on clean, reconciled, governed data. What You’ll Do Data Pipelines & Medallion Architecture Build andmaintainingestion pipelines from source systems (e.g., Dynamics, Workday, Airtable, SFTP feeds). • Design and implement Medallion pipelines (Bronze → Silver → Gold) across Finance and Hiring data. • Build reconciliation and gating logic to ensure only validated data reaches Gold. Multi-tenant Data Modeling Design multi-tenant PostgreSQL schemas with row-level security (RLS) for tenant isolation. • Implement SCD2 patterns for historical tracking of hiring/finance records. • Build cross-domain enrichment pipelines (e.g., Finance + Hiring joins for cost-per-FTE and related KPIs). APIs & Platform Integration Build and maintainFastAPIendpoints consumed by the UI and AI layers. • Partner closely with DevOps to deploy orchestrated pipelines on Azure (e.g., Prefect). What You Bring Qualifications & Experience 4+ years building production-grade data pipelines. • Strong PostgreSQL: schema design, RLS, triggers, window functions. • Strong Python for pipelines, transformations, and APIs. • Experience with orchestration tooling (Prefect/Airflow or similar). • Hands-on exposure to Medallion architecture and SCD2 in practice. Key Skills Data governance mindset—treat pipelines andGoldoutputs as platform contracts. • Strong debugging, performance tuning, and reliability orientation. • Comfort building for scale and reuse in a multi-tenant environment. What Success Looks Like – Global Excellence (GE) Data pipelines runpredictably—highreliability, clean promotions to Gold, minimal rework. • Tenant isolation is robust—RLS works consistently and safely at scale. • KPIs are reconcilable—Finance and Hiring views are accurate and auditable. • Downstream teams move faster—AI and UI features ship with confidence due to strong data foundations. If you enjoy building multi-tenant data foundations, designing pipeline contracts that scale, and enabling AI + dashboards with governed data — this role offers both impact and progression. Zinnov is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive workplace. We welcome applications from individuals of all backgrounds, communities, and experiences.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
