Data Platform Engineer

UNAVAILABLE; Argentina; Remote; ARS 1,200,000 - 2,400,000; Full time

Benefits offered by this job

Remote work

Job summary

Bridgenext is seeking a DataOps engineer to automate Databricks jobs/workflows, implement Unity Catalog at scale, and manage CI/CD pipelines across cloud platforms.

You will work in a fast-paced, distributed global team, driving reliability, data quality, and governance across the data stack. Remote-friendly with flexible collaboration across time zones.

Qualifications

• 5–8 years of experience in data engineering, platform engineering, or cloud infrastructure roles.
• Strong hands-on Databricks administration and workflow development experience.
• Proficiency in Terraform IaC, AWS cloud, and Python scripting.

Responsibilities

• Design, build, and maintain Databricks workflows and jobs with robust logging and governance.
• Implement and operate Unity Catalog at scale, including RBAC and audits.
• Lead CI/CD pipelines (GitHub Actions/Azure DevOps/GitLab) for IaC and data pipelines.

Skills

Databricks administration

Databricks workflows

Terraform

AWS

Python

Git

CI/CD

Agentic AI

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

#LI-AP1

#LI-REMOTE