Data Engineer

We are looking for an experienced Data Engineer with 2–7 years of experience in designing, developing, and maintaining scalable data pipelines and data processing systems. The ideal candidate should have strong expertise in Python, SQL, Apache Spark, ETL/ELT processes, and big data technologies. You will be responsible for building reliable data infrastructure and enabling data-driven business solutions.

Work Locations: New York City, NY | Seattle, WA | Chicago, IL
Employment Type: Full-Time
Work Arrangement: 100% Remote – Candidates must be eligible to work in the United States.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines.
• Build and optimize ETL/ELT workflows for large datasets.
• Develop data processing solutions using Python, SQL, and Apache Spark.
• Extract, transform, and load data from multiple sources.
• Design and maintain data warehouses and data lakes.
• Perform data validation, cleansing, and quality checks.
• Optimize SQL queries and data processing performance.
• Collaborate with Data Scientists, Analysts, and Software Engineers.
• Implement data integration and automation solutions.
• Monitor pipeline performance and troubleshoot data-related issues.
• Ensure data security, reliability, and consistency.

Required Skills

• 2–7 years of experience in Data Engineering.
• Strong programming skills in Python.
• Advanced knowledge of SQL and database management.
• Hands-on experience with Apache Spark and PySpark.
• Experience developing ETL/ELT pipelines.
• Knowledge of data warehousing and data modeling.
• Understanding of relational and NoSQL databases.
• Experience with data processing and transformation.
• Familiarity with Git and version control systems.
• Strong analytical and problem-solving skills.

Preferred Qualifications

• Experience with AWS, Azure, or Google Cloud Platform.
• Knowledge of Snowflake, Databricks, or BigQuery.
• Familiarity with Apache Airflow and workflow orchestration.
• Experience with Kafka and real-time data processing.
• Understanding of data lake and lakehouse architectures.
• Knowledge of Docker and CI/CD pipelines.
• Experience with distributed computing and big data technologies.

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field, or equivalent practical experience.

Compensation & Benefits

• Competitive compensation based on experience and skills.
• Health, dental, and vision insurance.
• Paid vacation and holidays.
• Remote work flexibility.
• Professional development and career growth opportunities.
• Opportunity to work with modern data engineering technologies.

Application Process

Interested candidates are encouraged to submit their updated resumes highlighting their Python, SQL, Apache Spark, PySpark, ETL pipelines, and cloud data engineering experience.