Architect - Data Engineering

2w2 weeks ago

Aubrant Digital

IN · Contract · INR 4,000,000 – INR 8,000,000

About this role

Aubrant Digital is a leader in multi-shore custom application development, passionate about solving clients’ business problems through consultative teamwork, innovative software, and proven processes. The Architect owns end-to-end delivery of data engineering on a flagship multi-year enterprise data transformation program. This builds a unified, governed data foundation on Azure with real-time CDC ingestion, master data management, and AI-ready analytics.

As a builder-leader, act as the technical bridge between customer senior technology leadership and Aubrant delivery team. Get hands-on with Databricks and pipeline code while leading the data engineering team. Pressure-test the team's QA approach yourself.

Own delivery against agreed architecture, requirements, and schedule; translate Unified Data Model into executable plans for source onboarding, ingestion patterns, ELT design, serving patterns, and quality gates. Drive sprint planning, milestone tracking, and execution across phased delivery. Identify risks, dependencies, and blockers early to manage commitments.

Aubrant executes full software lifecycle across offices in New Jersey, Boston, Costa Rica, and Eastern Europe. Culture emphasizes client service, trust-based relationships, and innovation, with high client retention and under 2% staff turnover. Serve over 50 clients with hundreds of custom enterprise applications.

Requirements

Working understanding of full target tech stack including Azure, Databricks, Delta Lake, and reference architecture validation
Hands-on experience with PySpark, Spark SQL for production ETL/ELT pipelines on Azure Databricks
Proficiency in configuring and extending Airbyte connectors for CDC ingestion
Expertise integrating API-based sources across SaaS, ERP, HRIS, and operational systems
Strong data modeling skills across enterprise domains handling identity, SCD, CDC, PII, and survivorship
Knowledge of real-time CDC ingestion, master data management, and AI-ready analytics foundations
Ability to translate business context into technical implications and vice versa for leadership

Responsibilities

Own end-to-end delivery of the data transformation against agreed architecture, requirements, and schedule
Translate the architecture and Unified Data Model into an executable plan: source onboarding, ingestion patterns, ELT design, serving patterns, and quality gates
Drive sprint planning, milestone tracking, and execution across the program's phased delivery
Identify risks, dependencies, and blockers early; drive resolution and manage scope and timeline commitments
Act as the day-to-day technical point of contact for customer leadership and engineering on progress, blockers, decisions, and solution alternatives
Run technical working sessions, design reviews, and walkthroughs that move decisions forward
Lead and contribute to data modeling across core enterprise domains; review for identity, SCD, CDC, PII, and survivorship correctness
Build production-grade ETL/ELT pipelines on Azure Databricks (PySpark, Spark SQL) with Delta Lake: ingestion, conformance, survivorship, and quality test layers