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, Power BI, and Python. This full-time, remote position requires collaboration with cross-functional teams to ensure data infrastructure reliability and scalability. Experience with Google Analytics and MLFlow is desirable but not required. You will leverage your expertise to build efficient ETL pipelines, optimize data workflows, and create compelling data visualizations. The role demands strong problem-solving skills and a collaborative mindset.

Requirements

• Be a US Citizen
• Have an active clearance at the Public Trust level or above. IRS is preferred
• Hold a Bachelor’s degree in Computer Science, Data Engineering, or a related field
• Have a minimum of 5 years experience as a Data Analytics Engineer, Data Engineer, or a similar role
• Possess expertise in Databricks, ETL Pipelines, and Python programming
• Demonstrate strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, Snowflake)
• Have a solid understanding of data warehousing concepts and cloud platforms (AWS, GCP, or Azure)
• Possess knowledge of data visualization tools such as Tableau and Power BI
• Have 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 and Power BI 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

• Have experience with Google Analytics
• Have familiarity with MLFlow in Databricks to manage machine learning models
• Have experience with big data frameworks such as Spark or Kafka
• Have knowledge of version control systems like Git and CI/CD pipelines for data workflows

Benefits

Remote work