Data Engineer: Build Modern Data Pipelines & Analytics

Description

We are looking for a motivated Data Engineer to join our growing data team. This role is ideal for a beginner-to-intermediate professional who is excited to help build, maintain, and optimize modern data pipelines, ensuring the organization has access to clean, reliable data. You will work closely with relational databases, cloud data warehouses, and modern orchestration tools while supporting analytics initiatives across the company.

This is a fantastic opportunity to level up your career using a modern data stack (Python, dbt, Dagster, Big Query) while enjoying a high degree of autonomy.

Requirements

Core Responsibilities

• Pipeline Development: Design, build, and optimize robust ETL/ELT data pipelines to ingest data from legacy ODBC databases and modern third-party APIs.
• Data Transformation: Write clean, optimized SQL and utilize DBT to transform raw data into production-ready models.
• Orchestration: Use Dagster to schedule, monitor, and manage workflows, ensuring errors are caught early.
• Database Management: Work across both SQL Server and Google Big Query, managing data structures and optimizing queries.
• Data Quality & Governance: Support data validation, troubleshooting efforts, and documentation of data governance best practices.
• Stakeholder Support: Collaborate with analytics teams to deliver clean datasets for reporting and support dashboard initiatives in Tableau or other BI Tools as required.
• Other duties as required.

• Experience: 1–3 years in data engineering, analytics engineering, or a data-heavy technical role.
• Strong SQL Skills: Proficiency in writing, debugging, and optimizing complex queries and stored procedures.
• Python Proficiency: Ability to write clean Python scripts for data manipulation, automation, and interacting with APIs.
• ETL/ELT Concepts: Solid understanding of data pipeline development and API/ODBC integrations.
• Technical Troubleshooting: Proven ability to troubleshoot data issues and work independently.

• Modern Data Stack: Familiarity with dbt (data build tool) and Dagster (or similar tools like Airflow).
• Google Cloud Platform (GCP): Familiarity with Big Query, Google Cloud Storage (Buckets), and Google Drive integrations.
• Data Visualization:
  
  Experience with Tableau or similar BI tools to understand downstream data consumption.
• Version Control: Basic experience with Git/Git Hub.
• Agile Mindset: Experience working in fast-paced environments with an interest in automation and process improvement.
• Agentic agent development knowledge is a plus.