Analytics Engineer

Key Responsibilities: Analyze source data and document comprehensive source-to-target mappings. Design, develop, and optimize scalable data pipelines utilizing Databricks, RDS PostgreSQL, Snowflake, and AWS services. Assess, monitor, and improve data quality and integrity across data workflows. Develop, troubleshoot, and enhance processes within data warehouse environments. Create reports using BI tools (e.g., Tableau, Sigma, Looker) and analytical notebooks (e.g., Jupyter Notebooks, JupyterLab). Collaborate closely with Data Analysts and Engineers, translating business requirements into technical solutions. Qualifications & Skills: Required: At least 3+ years of relevant experience in data engineering or analytics engineering. Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field. Strong proficiency in SQL and Python, including experience with libraries such as pandas for data manipulation and matplotlib, seaborn, or plotly for data visualization. Hands-on experience with Databricks, RDS PostgreSQL, and AWS. Familiarity with version control systems (Git) and data orchestration tools (Airflow). Experience developing reports using BI tools (Tableau, Sigma, Looker). Familiarity with analytical notebooks (e.g., Jupyter Notebooks, JupyterLab). Preferred: Experience with Snowflake highly desirable. Understanding and experience with Data Vault 2.0 architecture. Relevant industry certifications (e.g., Databricks Certified Data Engineer, Snowflake certification). Soft Skills: Exceptional problem-solving capabilities and strong attention to detail. Effective communication and collaboration skills across technical and non-technical teams. Ability to work independently, set priorities, and manage multiple projects in a fast-paced environment. Eagerness to learn and adapt in an ever-evolving tech landscape. Role Description: The Analytics Engineer will play a pivotal role bridging data analysis and engineering, responsible for developing, documenting, and optimizing data workflows. This role ensures seamless integration between business analytics and data infrastructure.

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