Data + Machine Learning Engineer
About Distillery
Distillery Tech Inc accelerates innovation through an unyielding approach to nearshore software development. The world’s most innovative technology teams choose Distillery to help accelerate strategic innovation, fill a pressing technology gap, and hit mission-critical deadlines. We support essential applications, mobile apps, websites, and eCommerce platforms by placing senior, strategic technical leaders and deploying fully managed technology teams that work intimately alongside our client’s in-house development teams. At Distillery Tech Inc, we’re not here to reinvent nearshore software development, we’re on a mission to perfect it.
Distillery Tech Inc is committed to diversity and inclusion. We actively seek to cultivate a workforce that reflects the rich tapestry of perspectives, backgrounds, and experiences present in our society. Our recruitment efforts are dedicated to promoting equal opportunities for all candidates, regardless of race, ethnicity, gender, sexual orientation, disability, age, or any other dimension of diversity.
About the Position
We are seeking a highly skilled Senior Data Engineer with experience in designing scalable data solutions and the ability to leverage machine learning techniques for
solving complex business problems. This role combines expertise in data engineering with advanced analytical capabilities, enabling you to work across the data lifecycle—from ingestion
and transformation to modeling and insights generation.
Responsibilities
● Data Architecture & Pipelines:
Design, develop, and optimize data pipelines and workflows for seamless data movement and processing.
Build and maintain scalable data architectures, including data warehouses (e.g.,
Snowflake, Redshift) and big data platforms (e.g., Databricks, Spark).
Implement ETL processes and automate data workflows to ensure high performance and reliability.
● Feature Engineering & Analytics:
Extract, transform, and manipulate datasets using SQL and Python to create features for analytics and machine learning.
Analyze large datasets to identify trends, insights, and opportunities for improving data systems and business processes.
Build dashboards and visualizations to communicate data insights and results effectively.
● Model Integration:
Develop, train, and deploy machine learning models within data pipelines to enhance predictive capabilities.
Ensure model scalability and performance when working with large datasets and distributed systems.
Utilize AWS tools (e.g., SageMaker, EMR) for managing machine learning workflows and data processing.
● Leadership & Collaboration:
Mentor junior team members on technical projects and coding best practices. Partner with stakeholders across analytics, product, finance, and marketing
teams to deliver end-to-end data solutions.
Actively participate in peer reviews, architectural discussions, and documentation efforts.
Requirements
Bachelor’s degree in Computer Science, Data Science, or a related field.
5+ years of experience in data engineering, focusing on large-scale data
pipelines and systems.
Expertise in SQL for complex data analysis and manipulation.
Strong programming skills in Python and shell scripting, with experience in Spark for distributed data processing.
Hands-on experience with ETL tools and cloud platforms like AWS (e.g., S3,
SageMaker, EMR).
Proficiency in working with relational databases and data warehouses (e.g., Snowflake, Redshift).
Ability to scale data processing and modeling solutions to handle millions of rows
efficiently.
Strong problem-solving skills with the ability to devise innovative solutions.
Excellent communication and interpersonal skills, capable of working with technical and non-technical teams.
Proven ability to work independently and manage priorities effectively in a
fast-paced environment.
Nice To Have
Familiarity with reporting tools like Tableau or similar platforms.
Experience working on subscription-based products.
Knowledge of accounting, FP&A, and marketing domains.