Data Engineer

Role Overview

• We are looking for a skilled and self-driven Data Engineer to join our engineering team. In this role, you will be responsible for building and maintaining the data infrastructure that powers analytics, reporting, and AI/ML workloads.
• You will work closely with BI Developers, AI/ML Engineers, and business stakeholders to ensure data is accurate, accessible, and pipeline-ready at all times.
• This role is ideal for someone who enjoys solving complex data movement and transformation challenges at scale - and takes pride in building systems that others can rely on.

Key Responsibilities

• Design, build, and maintain robust, scalable data pipelines (batch and streaming) for ingestion, transformation, and delivery
• Develop and manage ETL/ELT workflows to move data across sources, warehouses, and consumption layers
• Architect and maintain data warehouse and data lake structures optimized for performance and cost
• Ensure data quality, consistency, and integrity across all pipelines and storage layers
• Collaborate with BI Developers to provide clean, well-modeled, query-ready data
• Work with AI/ML Engineers to prepare, version, and serve feature-ready datasets
• Monitor, troubleshoot, and optimize pipeline performance and reliability
• Implement and enforce data governance practices - lineage, cataloging, access controls, and documentation
• Evaluate and recommend tools, technologies, and architectural improvements as data needs evolve

Required Skills & Qualifications

• 2+ years of hands-on experience in data engineering or a closely related role
• Strong proficiency in Python for data processing, pipeline development, and automation
• Solid command of SQL - complex transformations, performance optimization, and database management
• Hands-on experience with ETL/ELT tools such as Apache Airflow, dbt, Azure Data Factory, or similar
• Experience with cloud data platforms - Microsoft Azure (preferred), AWS, or GCP
• Working knowledge of data warehousing solutions - Azure Synapse, Snowflake, BigQuery, or Redshift
• Familiarity with big data technologies - Apache Spark, Databricks, or Kafka
• Understanding of data modeling concepts - normalized, dimensional, and lakehouse architectures
• Experience with version control (Git) and collaborative development practices
• Bachelor's degree in Computer Science, Information Technology, or a related field

Good to Have

• Exposure to real-time or streaming data pipelines (Kafka, Azure Event Hubs, or similar)
• Experience with containerization and orchestration - Docker, Kubernetes
• Familiarity with infrastructure-as-code or CI/CD practices in data environments
• Knowledge of data quality frameworks or tools (Great Expectations, Monte Carlo, etc.)
• Basic understanding of ML pipelines and feature stores
• Experience working in Agile or sprint-based delivery teams

Who Will Thrive in This Role

• Someone who is obsessed with reliability, thinks upstream before downstream, and finds satisfaction in building pipelines that simply never break.
• If you treat data as a product - not just a byproduct - this role is built for you.

What We Offer

• Work on diverse, complex, real-world data engineering challenges across industries
• Direct collaboration with BI, AI/ML, and product teams in an integrated data environment
• Structured growth path within a fast-scaling technology company
• A culture that values engineering excellence, ownership, and continuous learning