Description
Database Architect
Location: Bengaluru, India
Department: Database
Experience: 10-15
About Impact Analytics
Impact Analytics™ (Series D Funded) delivers AI-native SaaS solutions and consulting services that help companies maximize profitability and customer satisfaction through deeper data insights and predictive analytics. With a fully integrated, end-to-end platform for planning,
forecasting, merchandising, pricing, and promotions, Impact Analytics empowers companies to make smarter decisions based on real-time insights rather than relying on last year’s inputs to forecast and plan this year’s business. Powered by over one million machine learning
models, Impact Analytics has been leading AI innovation for a decade, setting new benchmarks in forecasting, planning, and operational excellence across the retail, grocery, manufacturing, and CPG sectors. In 2025, Impact Analytics is at the forefront of the Agentic AI revolution, delivering autonomous solutions that enable businesses to adapt in real time, optimize operations, and drive profitability without manual intervention. Here’s a link to ourwebsite: www.impactanalytics.co.
The impact that you will be making
The role would require you to develop sophisticated products that add value to the client and result in new projects and revenue streams.
What this role entail
▸ Architecture & Design
- Own database architecture decisions for 2–3 retail platform domains (e.g. pricing engine, demand forecasting, inventory) — bounded contexts, schema patterns, storage engine selection.
- Choose and apply the right data modelling pattern per workload: 3NF for OLTP, star/snowflake for analytics, Data Vault 2.0 for auditable historical data.
- Design the OLTP/OLAP split per domain — what lives in PostgreSQL vs ClickHouse vs the Lakehouse.
- Produce and maintain ERDs, data flow diagrams, and Architecture Decision Records (ADRs) for every significant schema change.
- Chair design reviews for your domains; approve schema migration PRs before they reach staging.
- Act as first escalation for production database incidents in your domain; write RCAs and preventive action plans.
▸ Hands-On Implementation
- Expert-level PostgreSQL: HA replication, multi-AZ clustering, advanced partition design, PITR, RLS, vacuum forensics, and query cost analysis.
- Design and implement ClickHouse table structures: MergeTree family selection, sharding, distributed tables, materialized views, projections, and TTL policies.
- Architect Lakehouse zones in Delta Lake / Apache Iceberg — schema evolution, time-travel, ACID guarantees on S3 / GCS.
- Implement observability: slow query dashboards, replication lag alerts, pipeline SLA tracking in GCP/DataDog.
▸ Team Guidance
- Guide Lead Engineers under your domain — review their designs, pair on hard problems, and give architecture-level feedback.
- Run data modelling workshops and query-tuning sessions for the engineering team.
- Define coding standards for SQL, pipeline code, and migration scripts used by your squad.
- Identify L&D gaps in Lead Engineers and recommend certification or upskilling paths.
▸ Cross-Functional Work
- Work with ML/Analytics/Product Engineers to define data contracts and feature pipeline requirements; design point-in-time correct read patterns.
- Enforce data security: RBAC, RLS, encryption at rest/transit, audit logging, GDPR/CCPA compliance across your domains.
Must Have
- 10–15 years hands-on: RDBMS development, big data engineering, and cloud architecture.
- Expert PostgreSQL — HA replication, advanced partitioning, RLS, PITR, vacuum tuning, performance forensics.
- Production Lakehouse ownership — Delta Lake or Apache Iceberg with medallion zone responsibility.
- Production ClickHouse or equivalent columnar OLAP in a retail / e-commerce context.
- Data modelling mastery: 3NF, star schema, snowflake, Data Vault 2.0 — right pattern per workload.
- Cloud: GCP (BigQuery, AlloyDB, Cloudsql, Dataflow).
- Python scripting for pipeline automation, data validation, and custom tooling.
- Experience guiding or mentoring junior/mid engineers on DB design — informal or formal.
Good to Have
- Retail domain knowledge: demand forecasting, pricing, promotions, inventory, or planogram data.
- Vector database awareness (pgvector, Weaviate, Pinecone) for LLM / RAG workloads.
- Data mesh / data product patterns in a large engineering org.
- GCP Professional Data Engineer, or Databricks certification.
What we offer
- An opportunity to develop some of the best enterprise SaaS products to be built out of India
- Opportunities to quench your thirst for problem-solving, experimenting, learning, and implementing innovative solutions
- A flat, collegial work environment, with a work hard, play hard attitude
- A platform for rapid growth if you are willing to try new things without fear of failure.
- Remuneration with best-in-class industry standards with generous health insurance cover.
Some of our accolades include:
● Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.
● Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.
● Voted #1 by more than 300 retailers worldwide in the RIS Software LeaderBoard 2024 report.
● Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune— alongside companies like Microsoft, Tesla, Apple, IBM, etc.
● Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.
● Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications.
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