Company Overview:

At Bridgenext, we engineer Growth Operating Systems. Most enterprises have spent millions on their revenue stack and still aren't seeing the growth they expected. They have tools that function, but no system that wins. We help growth-hungry companies close that gap by turning fragmented platforms, siloed teams, and disconnected data into one integrated Growth OS.

More than a technology company or marketing agency, we're a global digital consultancy with experts in engineering, data, AI, creative and more.

Our teams are made up of experts who believe in engineering impact, starting with putting people at the center of everything we do. Every team member directly shapes our work, culture, and values. Nothing matters more to us than a kind, respectful, fulfilling environment that supports everyone.

Our flexible, inclusive culture gives you the autonomy, resources, and opportunities to thrive.

Position Description:

We are looking for Data Ops engineer with a hands-on experience to automate our Databricks Jobs/Workflows, DLT, and SQL tasks, implement and operate Unity Catalog at scale.

Key Responsibilities

1. Automation & Orchestration (Jobs/Workflows & CI/CD)

- Design, build, and maintain Databricks Workflows/Jobs (multi‑task graphs, retries, triggers, alerts) for batch, and SQL workloads.
- Implement CI/CD pipelines (Git Hub Actions/Azure Dev Ops/Git Lab): plan/apply for IaC, validate job JSON, workplace promotion, approvals, and rollback.
- Build templatized, parameterized job definitions (ingestion/batch/streaming/SQL) with standardized logging, notifications, and governance.
- Enforce run‑as service principals, job versioning, change auditability, and artifact immutability.
- Automate provisioning via Terraform (Databricks provider), Databricks SDK (Python/Go), and REST API 2.1 for Jobs, DLT, Repos, SQL Warehouses, and Unity Catalog.

1.



Unity Catalog – Automation, Governance & Migration

- Catalog & Schema Provisioning (Automation‑first): Idempotent creation of catalogs, schemas, default locations, owners, grants, volumes, storage credentials, and external locations using Terraform/SDK/REST.
- Grant‑as‑Code: Standardize RBAC with templates (OWNERSHIP, USE CATALOG/SCHEMA, SELECT, MODIFY, CREATE, READ/WRITE FILES); integrate SCIM groups and service principals.
- Security & Audit: Dynamic views for row/column‑level security, data classification tags, audit logging, token policies, periodic permissions drift detection & remediation.
- Delta Sharing: Automate providers/recipients, share objects, and scheduled access reviews/expiry.
- Unity Catalog Migration (HMS → UC or multi‑workspace to UC): discovery, wave planning, external/managed table registration, permission model migration, dual‑run validation (row counts, schema parity, query replay), cutover & rollback.

1. Reliability & Data Quality

- Define SLOs for pipeline success, latency, and data freshness; drive ≥99% T1 success and low MTTR.
- Implement data quality checks (DLT expectations, dbt‑expectations/GX), idempotency, schema evolution strategy, checkpointing & replay.
- Build incident response playbooks; lead RCAs and preventative actions.

Required Qualifications

- 5–8+ years (Senior) across Data Ops for data platforms.
- Hands‑on Databricks: Workflows/Jobs, Delta Live Tables, Delta Lake, Repos, SQL Warehouses, cluster policies & pools.
- Unity Catalog automation expertise: catalogs, schemas, volumes, external locations, storage credentials, grants, Delta Sharing, audit & drift control.
- Terraform (Databricks provider) and Databricks SDK/CLI/REST for UC + platform automation; CI/CD with Git Hub Actions/Azure Dev Ops/Git Lab.
- Strong Python and SQL; Spark job configuration/tuning basics.

Bridgenext is an Equal Opportunity Employer

📌 Data Platform Engineer (Pune)
🏢 Nameless
📍 Pune