Data Engineer

DATA ENGINEER We are a global digital agency comprised of strategists, creatives, media experts, data scientists, and engineers driven by one common purpose — accelerate business growth through marketing and digital transformation. Named a top 3% Google Premier Partner and recognized by Inc. 5000 and Adweek’s 75 Fastest Growing Companies, we’re constantly looking for “A” players to join our team.

The rapid growth is attributed to our strongest asset — our people. Our teams are highly collaborative and work closely with each client to set clear goals and objectives so that we can deliver exceptional results. Mindgruve is a place where every opinion is valued. Not only will you be empowered to contribute ideas, but you will also play a key role in the execution and driving success for brands across a variety of industries. Sound fun? Perfect — you’ll fit right in.

Position Overview The Data Engineer plays a key role in building and maintaining reliable data pipelines that support analytics and business decisions. This position focuses on integrating data from multiple sources and transforming it into accurate, consistent, and accessible information.

Using Python, SQL, and cloud technologies—primarily AWS—the Data Engineer will work with APIs, databases, and files such as JSON, CSV, and Parquet. The role also supports data quality, monitoring, and the maintenance of data lakes and data warehouses.

This position is designed for someone with early professional experience who is ready to strengthen their technical skills, take ownership of data processes, and grow within a collaborative environment.

What You'll Do Here

• Build and maintain data pipelines that move information from multiple sources into storage and analytics platforms.
• Integrate, clean, normalize, and transform structured and unstructured data.
• Use Python and pandas to process data and connect to REST APIs.
• Write and optimize SQL queries using joins, aggregations, and window functions.
• Read, troubleshoot, and improve code and queries developed by other team members.
• Deploy and operate data solutions in AWS using services such as S3, Redshift, Lambda, and Glue.
• Support ETL/ELT processes, databases, data lakes, and data warehouses.
• Implement data quality checks, monitoring, validations, and alerts.
• Troubleshoot pipeline issues and improve performance and reliability.
• Document data sources, transformations, and technical processes.
• Collaborate with Data Science, Analytics, and Engineering teams.
• Follow data security, privacy, and governance standards.

Skills And Experience

• 1–2 years of professional experience in Data Engineering, Analytics Engineering, Backend Development, or a related role. Internship-only or academic-project-only experience does not qualify.
• Bachelor’s degree in Data Science, Computer Science, Software Engineering, Information Systems, or a related field.
• Strong Python skills, with the ability to write, read, and debug production code.
• Experience with pandas, REST APIs, and JSON, CSV, and Parquet data.
• Strong SQL knowledge, including joins, aggregations, and window functions.
• Ability to read, troubleshoot, and optimize SQL queries written by others.
• Hands-on experience deploying or operating solutions in a real cloud environment. AWS experience is strongly preferred.
• Understanding of ETL/ELT processes and relational databases.
• Strong problem-solving skills and attention to detail.
• Ability to work independently and collaboratively.
• Advanced English communication skills.

What We Consider As a Plus

• Experience with AWS services such as S3, Redshift, Lambda, or Glue.
• Familiarity with NoSQL databases and data orchestration tools such as Airflow.
• Experience with Git, CI/CD, automated testing, or Docker.
• Knowledge of Power BI, Tableau, or other data visualization tools.
• Familiarity with other cloud platforms, such as GCP or Azure.
• Knowledge of Java or another Backend Development language.