Job Overview

We are seeking a driven and detail-oriented Data Engineer to build, maintain, and optimize our data infrastructure and processing pipelines. In this role, you will be responsible for designing scalable data architectures, integrating disparate data sources, and building robust ETL/ELT pipelines to ensure reliable data flow for analytics and machine learning applications. You will collaborate closely with data analysts, software developers, and business leaders to empower data-driven decisions.

Responsibilities

  • Pipeline Architecture: Design, construct, and maintain scalable, reliable, and automated ETL/ELT data pipelines from structured and unstructured sources.
  • Data Warehousing: Build and optimize data models, schemas, and storage structures in modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift).
  • Data Quality & Governance: Implement automated data validation, quality checks, and monitoring systems to ensure data accuracy, security, and compliance.
  • Database Optimization: Perform performance tuning, index optimization, and query troubleshooting across relational and non-relational database systems.
  • Integration & API Management: Create and maintain custom APIs and connectors to ingest data from third-party tools, databases, and streaming services.
  • Cross-Functional Support: Partner with data analysts and data scientists to deliver production-ready datasets that support dashboards, reports, and machine learning models.

Skills & Qualifications

  • Programming & Scripting: Strong proficiency in Python, Scala, or Java for data processing and pipeline automation.
  • SQL & Data Modeling: Expert-level SQL skills with experience in dimensional modeling, data warehousing, and query optimization.
  • Data Engineering Frameworks: Hands-on experience with orchestration and orchestration tools (e.g., Apache Airflow, dbt) and big data frameworks (e.g., Apache Spark).
  • Cloud & Storage Platforms: Familiarity with major cloud environments (AWS, GCP, or Azure) and modern cloud data warehouses (Snowflake, BigQuery, or Redshift).
  • DevOps & Version Control: Proficiency with Git, CI/CD pipelines, containerization (Docker), and Infrastructure as Code principles.
  • Experience: High school diploma or equivalent required (Bachelor’s in Computer Science, Data Engineering, or related field preferred); 2–4+ years of data engineering or software development experience.

Benefits

  • Competitive Compensation: Base salary or hourly rate based on experience, with performance-based bonuses.
  • Health & Wellness: Comprehensive medical, dental, and vision insurance options.
  • Paid Time Off: Paid vacation, sick leave, and company holidays.
  • Flexible Work: Remote or hybrid scheduling options with flexible working hours.
  • Professional Growth: Annual learning stipend for data engineering certifications, technical workshops, and cloud provider accreditations.
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