Data Engineer + Python + Databricks + Spark

Improving; México; Presencial; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Improving is seeking a seasoned Data & Analytics Engineer to build data ingestion, transformation, and analytics pipelines using Spark on Databricks. You will deliver Spark-based solutions and design Databricks workflows.

The role requires 5+ years of hands-on software development, Python with PySpark and Pandas, and a solid understanding of Parquet and Delta Lake. You will work across teams to optimize data processing and contribute to testing and reliability.

Formación

• 5+ years hands-on software development experience.

Responsabilidades

• Build data ingestion, transformation, and analytics pipelines.
• Deliver Spark-based solutions on Databricks.
• Design and manage Databricks workflows.
• Develop and maintain unit tests for Databricks workloads.
• Handle small to large data volumes, including performance tuning and optimizations.

Conocimientos

Apache Spark

Python / PySpark

Pandas

Delta Lake

Parquet

Data pipelines

Herramientas

Databricks

Delta Lake

Parquet

Descripción del empleo

Improving is committed to building a great place to work by cultivating an environment that fosters professional and personal relationships. We value open communication, personal growth, and shared rewards, which result in sustainable success.

Voted “best place to work” numerous times, Improving strives to create and maintain a culture that exemplifies teamwork, excellence, and fun! We believe this kind of culture encourages both the inspiration and the motivation to achieve amazing things.

Data & Analytics

What you'll do

• Build data ingestion, transformation, and analytics pipelines
• Deliver Spark-based solutions on Databricks
• Design and manage Databricks workflows
• Develop and maintain unit tests for Databricks workloads
• Handle small to large data volumes, including performance tuning and optimizations

What you'll bring

• 5+ years of hands-on software development experience
• Strong expertise in Apache Spark, including delivery on Databricks
• Proficiency in Python with advanced data engineering skills using PySpark, Pandas, and related libraries
• Solid understanding of columnar storage (e.g., Parquet) and hands-on experience with Delta Lake / Delta Tables
• Strong analytical and problem-solving skills with close attention to detail
• Nice to have: Familiarity with Databricks DevOps practices

Improving welcomes people from all backgrounds and walks of life, and this is reflected in our largely diverse community of Improvers. Improving is proud to be an equal opportunity employer and is committed to providing equal opportunities for all employees and applicants. Improving recruits, hires, trains, promotes, compensates, and administers all personnel actions without regard to race, color, religion, sex, sex stereotyping, pregnancy (which includes pregnancy, childbirth, and medical conditions related to pregnancy, childbirth, or breastfeeding), gender, gender identity, gender expression, national origin, age, mental or physical disability, ancestry, medical condition, marital status, military or veteran status, citizenship status, sexual orientation, genetic information, or any other status protected by applicable law.

About Improving

Improving is a modern digital services company dedicated to positively changing the perception of the IT professional. We offer innovative solutions through consulting, software development, and training to help thousands of our clients achieve new heights in a competitive and ever-changing market.

As our company continues to grow, we are looking for enthusiastic thought leaders to join our team. Improving has a unique mix of passionate professionals who strive to grow and thrive in new ways. We are committed to establishing and maintaining an inclusive culture that allows all Improvers to bring their authentic selves to work each day. This is why we work hard to build inclusion and diversity in our workplace, so we can all do amazing things and succeed together.