Data Engineer - Python, SQL & BI

Salary is 110k to 120k We are looking for a skilled Data Engineer to design, build, and maintain reliable data pipelines and analytics solutions. You will work closely with data analysts, business teams, and engineering teams to transform raw data into accurate, actionable insights.

Salary is 110k to 120k

We are looking for a skilled Data Engineer to design, build, and maintain reliable data pipelines and analytics solutions. The ideal candidate has strong experience with Python, SQL, data warehousing, ETL/ELT processes, and Business Intelligence (BI).

You will work closely with data analysts, business teams, and engineering teams to transform raw data into accurate, actionable insights.

Responsibilities

• Develop and maintain scalable data pipelines using Python and SQL.
• Build ETL/ELT processes to collect, transform, and load data from multiple sources.
• Design and optimize data warehouses, databases, and data models.
• Write complex SQL queries for data transformation, analysis, and reporting.
• Ensure data quality, accuracy, security, and reliability.
• Support BI dashboards and reporting using tools such as Power BI, Tableau, or Looker.
• Partner with analysts and business stakeholders to understand data requirements.
• Troubleshoot data pipeline and performance issues.
• Automate repetitive data-processing and reporting tasks.
• Document data pipelines, processes, and data models.

Required Skills

• Strong programming experience with Python.
• Advanced SQL skills, including joins, CTEs, window functions, and query optimization.
• Experience building ETL/ELT pipelines.
• Knowledge of relational databases and data warehousing concepts.
• Experience with at least one BI platform such as Power BI, Tableau, or Looker.
• Understanding of data modeling, data quality, and database performance.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with AWS, Azure, or Google Cloud.
• Experience with Spark, Airflow, dbt, Snowflake, Databricks, or similar technologies.
• Familiarity with Git and CI/CD.
• Experience working with APIs and cloud-based data sources.
• Knowledge of dimensional modeling and modern data platforms.