Data Engineer

Evotym; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Evotym is seeking a Data Engineer to build and optimize scalable data pipelines and data infrastructure within a fintech context. You will own data lake maintenance, collaborate with cross-functional teams, and ensure data quality and availability across systems.

The role emphasizes hands-on data processing, ETL/ELT workflows, and modern tooling like Spark, Kafka, Airflow, and Docker in an AWS environment. Strong coding and problem-solving are required.

Qualifications

• Strong proficiency in Python and SQL.
• Hands-on experience designing, building, and maintaining scalable data pipelines and data processing solutions.
• Experience with ETL/ELT processes, including data ingestion, transformation, integration, and orchestration.
• Practical experience with AWS cloud services and cloud-based data infrastructure.
• Experience with Apache Airflow for workflow orchestration and scheduling.
• Hands-on experience with Docker and containerized environments.
• Solid understanding of data architecture, data quality, reliability, scalability, and data engineering best practices.
• Ability to write clean, efficient, testable, and maintainable code.
• Strong analytical, problem-solving, and critical-thinking skills with excellent attention to detail.

Responsibilities

• Develop, optimize, and maintain ETL pipelines and data ingestion processes.
• Take ownership of data lakes, including their maintenance and documentation.
• Transform complex data structures into machine-readable formats.
• Design and maintain databases and data infrastructure.
• Work with cross-functional teams to verify data relevance, quality and accuracy.
• Identify opportunities to improve reliability and efficiency of data processes.
• Collaborate with other departments to ensure data is usable and timely.

Skills

Python

SQL

ETL/ELT

Data pipelines

AWS

Airflow

Spark

Kafka

Data modeling

Git

Tools

Apache Spark

Apache Kafka

Apache Airflow

Docker

Job description

Our client is a provider of online payment processing solutions, focusing on a range of services including payment gateway services, global payment processing, and open banking. They serve online businesses across various sectors, supporting multiple currencies and payment methods.

As a Data Engineer, you will have the opportunity to work with cutting-edge technologies and make a significant impact on data processes within the fintech sector. This role involves developing scalable data pipelines, optimizing data infrastructure, and collaborating with cross-functional teams to ensure data accuracy and quality.

• Work with various data sources and integrate them into internal systems.
• Develop, optimize, and maintain ETL pipelines and data ingestion processes.
• Take ownership of data lakes, including their maintenance and documentation.
• Transform complex data structures into machine-readable formats.
• Design and maintain databases and data infrastructure.
• Work closely with other departments to verify the relevance, quality, and accuracy of data.
• Identify opportunities to improve the reliability and efficiency of existing data processes.
• Strong proficiency in Python and advanced SQL.
• Hands-on experience designing, building, and maintaining scalable data pipelines and data processing solutions.
• Strong experience with ETL/ELT processes, including data ingestion, transformation, integration, and orchestration.
• Practical experience with Apache Spark for large-scale data processing.
• Experience with Apache Kafka and event-driven/streaming data pipelines.
• Hands-on experience with database design, data modeling, optimization, and performance tuning.
• Practical experience with AWS cloud services and cloud-based data infrastructure.
• Experience with Apache Airflow for workflow orchestration and scheduling.
• Practical experience with Docker and containerized environments.
• Strong knowledge of Git and modern software development workflows.
• Solid understanding of data architecture, data quality, reliability, scalability, and data engineering best practices.
• Ability to write clean, efficient, testable, and maintainable code.
• Strong analytical, problem-solving, and critical-thinking skills with excellent attention to detail.
• Ability to work independently, prioritize effectively, and manage multiple tasks in a fast-paced environment.
• Experience in fintech
• Strong analytical and problem-solving skills with excellent attention to detail.
• Ownership mindset, proactivity, and ability to work independently and manage priorities.
• Strong communication and collaboration skills with the ability to work effectively across teams.
• Competitive salary aligned with experience
• Collaborative and transparent team culture
• High-impact role in a scaling fintech company
• Recognition of personal milestones and achievements