Data Engineer

SUMMARY:
Are you a forward-thinking Data Engineer with a passion for connecting the dots in data? Do you thrive on building high-performance data platforms that support diverse teams and business services?

POSITION INFO:
As a Data Engineer at our client, you’ll play a pivotal role in expanding and optimizing their data architecture and data pipeline systems. You’ll work with cutting-edge technology to build efficient data solutions that support cross-functional teams, improve processes, and unlock powerful insights for the business.

If you enjoy tackling complex data challenges, designing innovative solutions, and optimizing data systems from the ground up, this is the perfect opportunity for you.

Key Responsibilities:

• Data Architecture & Pipeline Optimization: Design and optimize data pipelines and architectures that handle large datasets and support multiple business services and teams.
• Cross-Functional Collaboration: Work closely with cross-functional teams to ensure data flows seamlessly, empowering teams with the information they need to make data-driven decisions.
• Big Data & Cloud Solutions: Build and optimize data solutions for “big data” environments, including cloud-based architectures and platforms.
• Root Cause Analysis & Process Improvement: Perform root cause analysis to identify issues with data and processes, providing solutions to optimize systems and improve data accuracy.
• Data Transformation & Metadata Management: Build processes supporting data transformation, metadata management, and workload management, ensuring the scalability and reliability of data systems.
• Platform Operations: Oversee operational aspects of data platforms, including monitoring, alerts management, and capacity planning.
• Leadership & Mentorship: Lead and mentor team members while supporting ongoing development and operational needs.

• 3+ years of experience in developing data solutions, including design, coding, testing, deploying, and supporting applications.
• A Degree in Computer Science, Applied Mathematics, Physics, Statistics, or a related field, or equivalent experience in data engineering or data science.
• Proficiency in SQL & Python, with experience working with relational databases and writing complex queries.
• Expertise in building and optimizing big data pipelines and architectures.
• Solid understanding of data application architecture and experience with business process modeling.
• Ability to perform root cause analysis on data and processes to uncover business opportunities and areas for improvement.
• Hands-on experience in manipulating and processing large datasets from disparate sources.
• Familiarity with message queuing, stream processing, and scalable data stores in a big data environment.
• Strong project management skills with a proven ability to prioritize and manage complex tasks.
• Previous experience supporting cross-functional teams and mentoring/leading data teams.
• Experience in Fintech data is a plus, but not required.