Analytics Engineer

Job Description

As a Data Engineer: Design, develop, and optimize our data pipelines and ETL processes. Maintain and enhance our Redshift data warehouse, ensuring efficient query performance, scalability,glue and uptime. Collaborate with cross functional teams to integrate data from various sources into our warehouse. Monitor Redshift upmetrics, improve query execution times, and reduce errors to ensure high availability and reliability. Implement best practices for data governance, security, and data quality. As a Data Analyst: Translate complex data into actionable insights for stakeholders across departments. Create dashboards and reports to visualize key performance indicators (KPIs) and business metrics. Perform ad hoc data analysis to support business decisions. Analyze data trends and provide recommendations to optimize business strategies and operations. Work closely with leadership to ensure data driven decisions are made in alignment with business goals. Requirements: Experience: 2-3 years in Data Engineering and/or Data Analytics roles. Skills Required: Skills in Data Engineering: Proficiency in SQL, ETL pipelines, and database management. Strong experience with cloud based data warehouses, particularly Amazon Redshift. Familiarity with data orchestration tools like Airflow or DBT. Knowledge of Python or similar programming languages for data processing. Skills in Data Analytics: Strong analytical skills with experience in data modeling and visualization tools (e.g., Tableau, Power BI, or Looker). Ability to derive actionable insights from large datasets. Experience working with key business metrics and KPIs. Bonus: Experience with AWS services, Spark, or other big data tools. Excellent problem solving skills and the ability to adapt to a fast paced environment. Strong communication skills to work cross-functionally with technical and nontechnical teams.