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Data Platform Engineer

Role overview

Summary

This role focuses on automating and optimizing data workflows at Bridgenext, enhancing the efficiency of Databricks and Unity Catalog operations. You will work within a team dedicated to integrating fragmented data systems, ensuring high reliability and data quality for clients seeking growth.

Qualifications

  • 5–8 years of experience in data engineering, platform engineering, or cloud infrastructure roles.
  • Strong hands-on experience with Databricks administration.
  • Proficiency in Terraform for infrastructure as code.
  • Solid experience with AWS cloud services and architecture.
  • Good Python scripting skills for automation and tooling.

Responsibilities

  • Automate Databricks Jobs/Workflows, DLT, and SQL tasks.
  • Design, build, and maintain Databricks Workflows/Jobs for batch and SQL workloads.
  • Implement CI/CD pipelines for Infrastructure as Code and job validation.
  • Automate provisioning via Terraform and Databricks SDK.

Key facts

Hard skills

Other skills

  • Problem Solving
  • Collaboration
  • Communication

About the company

Bridgenext logo

Bridgenext

  • IT Services & Consulting
  • Large
  • 1,001–5,000
Bridgenext is a global digital consultancy that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need. Our global consulting and delivery teams across the U.S., Canada and India facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services.

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Job description

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 DataOps engineer with hands-on experience to automate our Databricks Jobs/Workflows, DLT, and SQL tasks, implement and operate Unity Catalog at scale. 

Key Responsibilities:

  • 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 (GitHub Actions/Azure DevOps/GitLab): plan/apply for IaC, validate job JSON, environment promotion, approvals, and rollback. 
    • Build templates, 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. 
  • 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. 
  • 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. 

Must Have Skills:

  • 5–8 years of experience in data engineering, platform engineering, or cloud infrastructure roles.
  • Strong hands-on experience with Databricks administration (workspace management, cluster policies, access controls, cost optimization).
  • Working knowledge of Databricks workflow development (job orchestration, scheduling, pipeline monitoring).
  • Proficiency in Terraform for infrastructure as code and automated provisioning.
  • Solid experience with AWS cloud services and architecture.
  • Good Python scripting skills for automation and tooling.
  • Good understanding of CI/CD practices and version control (Git).
  • Exposure to or experience implementing Agentic AI solutions, Genie spaces and apps primarily or anything similar.

Professional Skills:

  • Strong problem-solving skills and ability to work in a collaborative, fast-paced environment.
  • Excellent English communication skills

Bridgenext is an Equal Opportunity Employer

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#LI-REMOTE

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