We are seeking a results-oriented Data Analytics Engineer who can bridge the gap between data wrangling/ETL and business intelligence. The core of this role is using Python (Pandas, NumPy) and PySpark on Databricks to curate, transform, and prepare clean datasets. Strong BI skills in Power BI/Tableau are also required, but as a complement to Python-driven data processing. The ideal candidate will have a mix of hands-on data engineering experience and business analysis skills, ensuring that dashboards and insights are built on reliable, well-structured data.

Data Engineering & ETL (Primary)

• Design, build, and maintain ETL pipelines using Python/PySpark on Databricks for ingestion, wrangling, and transformation.
• Implement data quality checks, validation rules, and performance optimization in ETL processes.
• Collaborate with IT and data engineering teams for UAT of package tables and seamless system integration.
• Build reusable, scalable datasets that support advanced analytics and BI reporting.

Business Intelligence & Visualization (Secondary)

• Develop and maintain interactive dashboards and reports in Power BI/Tableau for leadership and stakeholders.
• Enable self-service analytics by curating structured datasets and reusable data sources.
• Present complex findings through clear, compelling visualizations tailored for business decision-making.

Analytics & Insights

• Perform exploratory data analysis (EDA) using Python (Pandas, NumPy) to identify trends, anomalies, and opportunities.
• Partner with business stakeholders to define KPIs, metrics, and reporting frameworks.
• Provide actionable, data-backed recommendations to drive strategy and performance.

Required Skills & Qualifications

• Strong programming skills in Python (Pandas, NumPy) for data wrangling and automation.
• Hands-on experience with PySpark and Databricks for ETL workflows.
• Expertise in SQL (Teradata, Databricks SQL, or similar).
• Proven experience in ETL development and scalable data workflows.
• Proficiency in Power BI/Tableau for visualization and dashboarding.
• Familiarity with data lake and data warehouse concepts.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field.
• 5 years of experience in analytics, data engineering, or BI, with demonstrated use of Python for ETL/wrangling.
• Track record of delivering insightful dashboards built on well-structured, Python-curated datasets.