Software Engineer II

Job Description Role: SE II Location: Bengaluru What you’ll do We’re MiQ, a global programmatic media partner for marketers and agencies. Our people are at the heart of everything we do, so you will be too. No matter the role or the location, we’re all united in the vision to lead the programmatic industry and make it Better. As a Software Engineer II on the Data Ingestion team, you'll drive the design, development and maintenance of large-scale data ingestion pipelines that power MiQ's programmatic advertising business. You will build automated, scalable and resilient pipelines that bring data in from a wide variety of external partners — DSPs (The Trade Desk, DV360, Amazon, Meta, Yahoo, Google Ads, Beeswax, Index Exchange, Magnite/ClearLine, Adsmovil, OMC, and more), SSPs, measurement and enrichment partners (Pixalate, Pixability, Vizio, Evertune, Lifesight, Circana, Experian) — into MiQ's centralised Databricks lakehouse and Unity Catalog. Day to day you'll work on: • Building and productionising ingestion pipelines on Databricks (PySpark notebooks, SDP, Autoloader, Delta etc) and orchestrating them via our scheduling and ingestion services. • Contributing to our Unified Ingestion Service contributing to our vision for Self Serve Ingestion • Onboarding new DSPs, regions, and third-party feeds; expanding reporting granularity and coverage across regions. • Strengthening Data Health, llineage, and incident management workflows. • Compliance and governance workflows • Release management and platform hygiene — Bitbucket/GitHub, CMRs, Terraform-managed IAM, Snyk/Akto vulnerability remediation. Who are your stakeholders? Key stakeholders include MiQ's Trading and Programmatic Ops teams, Analytics and Data Science, Product Management, Data Management & Data Governance, the Platform and IT/DevX teams, Regional Delivery and Account Management, external DSP/SSP and measurement partners, and other Data Ingestion pods responsible for downstream reporting and activation. What you’ll bring • 2–3 years of experience in data engineering and data integration, with hands-on exposure to building and managing data pipelines on cloud platforms (AWS preferred; Azure or GCP acceptable). • Extensive hands-on experience with PySpark notebook development (preferably on Databricks) and advanced SQL to build and optimise large, high-throughput data pipelines. • Strong working knowledge of the modern lakehouse stack — Delta Lake, Delta Live Tables (DLT), Autoloader, Unity Catalog — and Hadoop-era tooling (Hive, Spark) is a plus for migration work. • Solid understanding of data modelling, schema evolution, and data transformation techniques, with a bias for data quality, reliability and integrity. • Comfortable with ingestion patterns across APIs, S3, SFTP/FTP, email drops, event streams and CDC. • Well-versed with SDLC, release management and incident management using Bitbucket/GitHub, JIRA, and change-management (CMR) workflows;…