Senior Data Engineer

About the role

PetroApp is looking for a Senior Data Engineer to design, build, and maintain scalable data pipelines that power our mobile, payment, and operational systems. You will work closely with analytics, product, finance, and operations teams to deliver reliable, high‑performance data solutions.

Key responsibilities

• Design and operate batch and near‑real‑time pipelines for mobile apps, NFC/fuel transactions, ERP, payments and partner integrations.
• Create reusable data models for core entities such as customers, vehicles, drivers, stations, transactions, wallets and invoices.
• Implement data validation, lineage, observability, alerting and automated quality checks to ensure accurate dashboards.
• Partner with cross‑functional teams to provide self‑service datasets, metric layers and well‑documented data marts.
• Optimize queries, storage layouts and cloud resources to improve performance and control costs.
• Apply data governance, PII handling, retention policies and auditability throughout the data lifecycle.
• Build robust ingestion patterns for APIs, webhooks, CDC, files, event streams and third‑party feeds.
• Use CI/CD, version control and infrastructure‑as‑code to standardize data pipeline deployments.
• Lead incident response, root‑cause analysis and knowledge sharing across the team.

Required profile

• 5+ years of professional experience in data engineering, analytics engineering or platform engineering.
• Strong ownership of data products and a track record of delivering production‑grade pipelines.
• Ability to mentor junior engineers and raise engineering standards.

Required skills

• Advanced SQL (query optimization, window functions, large‑table tuning).
• Python for data pipelines, automation and testing.
• Workflow orchestration tools (Airflow, Dagster, Prefect or similar).
• Modern data warehouses or lakehouse platforms (BigQuery, Snowflake, Redshift, Databricks, Delta Lake, Iceberg).
• ELT/ETL tooling (dbt, Spark, Kafka, Flink, Fivetran, Stitch, CDC frameworks).
• Cloud platforms (AWS, GCP, Azure) and Git‑based engineering workflows.
• CI/CD, version control and infrastructure‑as‑code practices.