Data Engineer

• Data Pipeline Development: Assist in designing, building, and maintaining automated ETL/ELT pipelines to ingest structured and unstructured data from internal APIs, databases, and third-party systems.
• Database & Query Optimization: Write efficient, maintainable SQL queries, views, and stored procedures. Troubleshoot slow-running queries and optimize database indexing.
• Data Modeling & Storage: Support the team in designing clean, scalable relational data schemas and star/snowflake schemas for enterprise data warehousing.
• Data Quality & Testing: Implement validation checks, unit tests, and monitoring to ensure data accuracy, completeness, and freshness across pipelines.
• Cross-Functional Collaboration: Partner with Data Analysts, Data Scientists, and Software Engineers to deliver clean, actionable datasets for reporting and ML models.
• Documentation & Best Practices: Maintain technical documentation for data workflows, lineage, schema definitions, and runbooks. Maintain code quality through Git version control and code reviews., * Mentorship & Growth: Direct mentorship from Senior Data Engineers and technical leads to accelerate your career.

We are seeking a motivated, detail-oriented Entry-Level Data Engineer to join our growing data engineering team. In this role, you will work alongside senior engineers to design, build, and maintain robust data pipelines, data warehouses, and data models that drive analytics across the organization.

This is an excellent opportunity for a recent computer science or data-focused graduate (or self-taught professional) with strong foundational skills in Python, SQL, and relational databases who is eager to scale their skills in cloud platforms and modern data technologies., * Education: Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related field (or equivalent hands-on project experience).

• SQL: Strong proficiency in writing SQL queries (joins, aggregations, CTEs, subqueries, indexing concepts).
• Programming: Proficient in Python (preferred) or Java/Scala for data processing and automation scripts.
• Database Fundamentals: Good understanding of relational database management systems (e.g., PostgreSQL, MySQL, SQL Server) and dimensional data modeling concepts.
• Version Control: Basic familiarity with Git and standard pull request workflows.
• Problem-Solving: Strong analytical mindset with high attention to detail and a passion for finding efficient solutions to data anomalies.

Nice-to-Have (Bonus Skills):

• Familiarity with modern data warehouse platforms (e.g., Snowflake, BigQuery, AWS Redshift, or Databricks).
• Basic exposure to workflow orchestration tools (e.g., Apache Airflow, Prefect, or dbt).
• Understanding of cloud services (AWS S3/Lambda, Azure Blob/Functions, or GCP Cloud Storage).
• Familiarity with containerization (Docker) or CI/CD pipelines.

• Modern Tech Stack: Hands-on exposure to production cloud architecture and modern data engineering tools.
• Competitive Package: [Insert Base Salary / EMI/Bonus Structure / Benefits / 401(k) / Health Insurance].
• Flexible Work Environment: [Insert Remote / Hybrid schedule details].

Pay: From $114,000.00 per year