About Truelogic
At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.
Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.
By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.
Our Client
At our company, we are committed to building cutting-edge solutions that drive efficiency and innovation. We thrive on a culture of continuous learning, collaboration, and proactive problem-solving. If you’re looking for a place where you can grow and make an impact, this is the team for you!
Job Summary
We are looking for a Junior to Semi-Senior PySpark Data Engineer who is eager to learn, take initiative, and contribute to the development of high-performance and scalable data pipelines. This role is perfect for someone who wants to enhance their technical skills while working on exciting projects within a collaborative team.
Responsibilities
Design, develop, and optimize data pipelines using PySpark and Apache Spark.
Integrate and process data from multiple sources (databases, APIs, files, streaming).
Implement efficient data transformations for Big Data in distributed environments.
Optimize code to improve performance, scalability, and efficiency in data processing.
Collaborate with Data Science, BI, and DevOps teams to ensure seamless integration.
Monitor and debug data processes to ensure quality and reliability.
Apply best practices in data engineering and maintain clear documentation.
Stay up to date with the latest trends in Big Data and distributed computing.
Qualifications and Job Requirements
1-3 years of experience working with PySpark and Apache Spark in Big Data environments.
Experience with SQL and relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, etc.).
Knowledge of ETL processes and data processing in distributed environments.
Familiarity with Apache Hadoop, Hive, or Delta Lake.
Experience with cloud storage (AWS S3, Google Cloud Storage, Azure Blob).
Proficiency in Git and version control.
Strong problem-solving skills and a proactive attitude.
A passion for learning and continuous improvement.
What We Offer
100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection.
Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.
Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed.
Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.
Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.
Why You’ll Like Working Here
A Culture That Values You: We prioritize well-being and work-life balance, offering engagement activities and fostering dynamic teams to ensure you thrive both personally and professionally.
Diverse, Global Network: Connect with over 600 professionals in 25+ countries, expand your network, and collaborate with a multicultural team from Latin America.
Team Up with Skilled Professionals: Join forces with senior talent. All of our team members are seasoned experts, ensuring you're working with the best in your field.
Apply now!