Forward Deployed Engineer

About Saras Analytics

Saras Analytics is an AI and data analytics firm built for ecommerce and omnichannel brands. We help fast-growing SMBs and mid-market brands turn disconnected, messy data into decisions — covering ingestion, transformation, and consumption, backed by our own products (Daton and Saras IQ) as the data infrastructure in every engagement.

Why Now

Saras is profitable and bootstrapped. We run flat: talent and good ideas move fast here regardless of tenure or title. AI-assisted tooling now lets one engineer take a client from requirements to a live, trusted dashboard without a queue of hand-offs — and the Forward Deployed Engineer role is built around exactly that. Joining now, you help define what the role looks like at its best.

The Role

You'll own the solution and the build for one client account, reporting to an FDE Lead. On that account you work alongside a Strategic Account Manager, who owns the client relationship and the commercial outcomes, and a Product Manager, who owns product onboarding, enablement, and roadmap. You own what gets built and whether it is right — requirements, data, metrics, dashboards, and data quality — with our AI-assisted tooling and our SME leads behind you for the hardest problems.

The Bar

Speed & Delivery quality are the top priorities for this role: what you ship is correct, validated against the source of truth before the client sees it, and there on the date you committed to. Speed matters because clients feel it — the shortest path from signed-off requirements to a live, trusted dashboard — but never at the cost of numbers the client can rely on. You surface risks before they block delivery, and you close every issue with a root cause and a fix, you internally escalate the dependencies on time. The lanes are explicit: you own the solution and the build; the Account Manager owns the relationship and the commercial outcomes; the Product Manager owns product onboarding, enablement, and roadmap.

What You'll Own

• Requirements. Run discovery on the client's core use cases, write the requirements and metric definitions, and track change requests so scope stays visible.
• The data build. Build staging, master, and presentation datasets with Saras' AI-assisted tooling on dbt and BigQuery, following our data-model conventions.
• Metrics and dashboards. Configure one certified set of metrics for the client, and build the dashboards and AI-analyst context that draw on it.
• Validation. Reconcile every dataset against its source, set up data-quality checks, and walk your Account Manager through the build before it reaches the client.
• Data quality, every day. Run the daily data-quality cycle, resolve issues before the client's day starts, and close every bug with a root cause and a fix.
• Partnership. Give your Account Manager the technical answers behind success criteria and adoption, and bring the product asks you hear to the Product Manager.

What Winning Looks Like

First 90 days: you know your account's data and definitions in depth, run the daily data-quality cycle reliably, and have taken one deliverable from signed-off requirements to a validated, live dashboard.

Steady state: you deliver independently and on time, your validation catches issues before the client does, and you're ready to own a new account launch end to end.

Who Thrives Here

You bring 3+ years (typically 3–6) of hands-on data work — some of it building in SQL, some of it facing clients — as a business or data analyst ready to own the build, an analytics or data engineer ready to own the client conversation, or a data consultant who has delivered end to end. You also have:

• A degree from a reputed engineering college.
• Strong SQL and data-modelling skills, plus hands-on experience with at least one BI tool.
• Working knowledge of dbt, BigQuery, and Git — or the ability to ramp up quickly.
• Comfort with AI-assisted development tools such as Cursor or Claude.
• The ability to turn an ambiguous ask into clear, testable requirements, and to own the client conversation.

It's an even stronger fit if you also bring:

• An engineering degree in Computer Science, AI, Data Analytics, or Data Science.
• Ecommerce data fluency — contribution margin, customer cohorts, attribution, inventory.
• Experience with a semantic layer or data-quality frameworks.

Location

Hyderabad. Standard working hours are noon to 9 PM IST.

Compensation & Benefits

Competitive salary with performance-based bonuses, comprehensive health insurance, relocation support, and ongoing professional development. Saras Analytics is an equal opportunity employer committed to building an inclusive workplace for all.

If you want to own what gets built, end to end, and see it land with the client, we want to talk to you.