Senior Data Engineer / ML Engineer

Who We Are

Lumicode Sp. z o.o. is part of the Pentacomp Group, a provider of IT solutions and professional IT services for large enterprises and the public sector.

As Pentacomp, we create IT solutions that combine innovation with years of experience - and we have quite a lot of it. We've been in the market for nearly 30 years and have successfully delivered many projects.

For our Client, a leader in the banking industry, we are looking for an experienced Senior Data Engineer/ML Specialist.

Tech Stack:

• Core: Python, Apache Spark, SQL

• Cloud (AWS): S3, Glue, SageMaker, Lambda, StepFunctions, MWAA/Airflow

• ML Frameworks: TensorFlow, PyTorch

• Tools: Git, BitBucket, Docker, CI/CD tools

Responsibilities:

• Managed the lifecycle of machine learning models from development to deployment and   monitoring, ensuring optimal performance and reliability.

• Implemented MLOps principles, including continuous integration, continuous delivery, testing, and monitoring, to streamline machine learning operations.

• Working with Spark & Python to define and maintain data ingestions and transformation, handling both real-time and batch data processing.

• Building distributed and highly parallelized big data processing pipeline which process massive amount of data (both structured and unstructured data) in near real-time.

• Leverage Spark to enrich and transform corporate data to enable searching, data visualization, and advanced analytics.

• Collaborated with cross-functional teams, including data scientists, DevOps engineers, and IT, to deliver high-quality machine learning solutions.

• Working closely with analysts and business stakeholders to develop analytics models.

• Help in optimizing our current MLOps practices and libraries, make applicable for wider range of use cases outside propensity models.

• Cloud solution exploration for AI/ML areas.

Must-have Requirements:

• Experience: Minimum 5 years of proficiency in Python and Spark.

• AWS Mastery: Strong hands-on experience with AWS services for ML and data processing (specifically S3, Glue, SageMaker, Lambda, StepFunctions/Airflow/MWAA) covering data ingestion, training, and automation.

• Infrastructure as Code: Practical understanding of AWS infrastructure setup and automation using AWS CLI, boto3, and IAM roles to ensure secure and reproducible workflows.

• ML Expertise: Experience with frameworks like TensorFlow or PyTorch (training, refining, and deploying models). Solid understanding of algorithms, data structures, statistics, and linear algebra.

• Big Data Knowledge: Deep understanding of distributed systems (Hadoop/Hive ecosystem) and SQL (Spark/Hive SQL).

• Methodology: Experience with Git/BitBucket and working in Agile/SAFe frameworks.

Nice to have

• Experience in designing and implementing specific ML Models such as Propensity, Customer Lifetime Value (CLV), Micro-segmentation, or channel recommendation models.