Data Analytics Engineer

Summary

Join LightFeather's dynamic team as a highly skilled Data Analytics Engineer! You will design, implement, and maintain scalable data pipelines and analytics solutions using Databricks, Tableau, and Python. Collaborate with cross-functional teams to ensure data infrastructure reliability and scalability. This is a full-time, remote position requiring US citizenship and a Public Trust clearance (IRS preferred). Experience with Google Analytics and MLFlow is desirable but not mandatory. LightFeather offers a commitment to diversity and inclusion.

Requirements

• US Citizenship
• Active clearance at the Public Trust level or above. IRS is preferred
• Bachelor’s degree in Computer Science, Data Engineering, or a related field
• Minimum of 5 years experience as a Data Analytics Engineer, Data Engineer, or a similar role
• Expertise in Databricks, ETL Pipelines, and Python programming
• Strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, Snowflake)
• Solid understanding of data warehousing concepts and cloud platforms (AWS, GCP, or Azure)
• Expertise in data visualization tools such as Tableau
• Excellent problem-solving skills, attention to detail, and a collaborative mindset

Responsibilities

• Architect, develop, and maintain efficient and scalable ETL data pipelines using Databricks and Apache Airflow to automate workflows and transform raw data into actionable insights
• Collaborate with stakeholders to gather business requirements and translate them into technical specifications and scalable solutions
• Develop and optimize advanced data workflows for performance, scalability, and cost-effectiveness
• Design and implement rigorous testing, validation, and monitoring strategies to ensure data quality, accuracy, and integrity
• Build, maintain, and enhance data visualization solutions using Tableau to support business intelligence needs
• Leverage MLFlow in Databricks to manage machine learning model lifecycles and integrate analytics into predictive pipelines (if applicable)
• Monitor and troubleshoot workflows, ensuring smooth operation and minimal downtime of Databricks pipelines and Airflow DAGs
• Stay up-to-date with the latest tools and advancements in data engineering, analytics, and visualization, continuously improving systems and processes
• Maintain comprehensive documentation for all data pipelines, workflows, and configurations to support knowledge sharing and long-term maintenance

Preferred Qualifications

• Experience with Google Analytics is highly desirable but not mandatory
• Familiarity with MLFlow in Databricks to manage machine learning models is a strong plus
• Experience with big data frameworks such as Spark or Kafka
• Knowledge of version control systems like Git and CI/CD pipelines for data workflows

Benefits

This is a Full Time, Remote Position