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About the Role

We are looking for a Senior Data Engineer to design and build scalable data lakes, warehouses, and lakehouse architectures supporting a thematic research platform that processes large volumes of financial data daily. You will implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ingestion workflows from third-party APIs, and work with Snowflake, Spark, and AWS to deliver high-performance data infrastructure. The role combines hands-on engineering with technical consulting responsibilities, translating business goals into data architecture roadmaps.

Responsibilities

Design and implement Python Data Engineering solutions
Design and build scalable Data Lakes, Data Warehouses, and Data Lakehouses
Design and implement robust ETL/ELT processes at scale using Python, incorporating modern pipeline orchestration tools like Airflow
Develop sophisticated ingestion workflows from diverse 3rd party APIs and data sources
Manage and optimize various file formats (Parquet, Avro, ORC) and columnar storage to ensure high-performance data retrieval
Work with AI development tools to support and accelerate ongoing development, machine learning initiatives and advanced analytics
Act as a technical consultant for stakeholders and leadership to gather requirements, understand business goals, and translate them into technical roadmaps
Work with Terraform and other tools to build AWS and on-prem infrastructure

Requirements

Must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time
5+ years of experience with Python (strong, hands-on Python experience is a must)
5+ years of experience with data processing, manipulation, and analytics libraries like Pandas, Polars, PySpark or DuckDB
2+ years of experience with Big Data technologies (Spark, Snowflake)
Expert-level knowledge of pipeline orchestration using Airflow or similar industry-standard tools
Deep understanding of Medallion Architecture, columnar file formats, and diverse database technologies (SQL, NoSQL, and Lakehouse architectures)
Proven ability to work with 3rd party APIs for complex data ingestion tasks
Proficiency with modern Cloud platforms (AWS, GCP, Snowflake) and advanced SQL optimization
Exceptional soft skills with a proven ability to gather requirements from leadership and collaborate effectively across cross-functional teams
Excellence in optimizing complex data pipelines and troubleshooting data latency or consistency issues in massive datasets
A self-starter mindset, regularly investigating more efficient data architectures and AI development tools to improve pipeline performance
Taking pride in data integrity and the accuracy of the end-to-end pipelines and architectures you build
Strong communication skills for seamless global collaboration with stakeholders and distributed teams
Upper-intermediate English level

Skills

Python
Data Lakes
Data Warehouses
Data Lakehouses
ETL/ELT
Airflow
API integration
Snowflake
Spark
AWS
Terraform
Pandas
Polars
PySpark
DuckDB
SQL
NoSQL
Cloud platforms
GCP
Medallion Architecture
Columnar file formats
Scala

Location

Remote
Office options

Work Type

Remote
Office options
Flextime

Experience Level

Senior

Education Level

Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience

Benefits

Mentorship
TechTalks
Personalized growth roadmaps
Competitive compensation
USD-based pay
Education budgets
Fitness budgets
Team activity budgets
Modern solutions with Fortune 500 and top product companies
Flexible schedule

About the Company

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries.
We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.