Senior Data Engineer

Summary

Join Method, a global design and engineering consultancy, as a Data Engineer to collaborate on data strategy and implementation projects. You will assess data and systems, identify data quality gaps, and contribute to data platform modernization. This B2B contractor role requires delivering services under a commercial contract and handling all tax, benefit, and insurance obligations independently. Responsibilities include working with various teams to deliver data solutions, analyzing existing systems, developing process maps, creating data catalogs, identifying data inconsistencies, recommending solutions for data standardization, and proposing database design standards. The role requires strong problem-solving skills, experience with requirements gathering, and excellent communication skills. The position is remote across Poland.

Requirements

• Strong problem-solving abilities with meticulous attention to detail and experience
• Experience with requirements gathering and methodologies
• Excellent communication and presentation skills with the ability to clearly articulate technical concepts, methodologies, and business impact to both technical teams and clients
• A unique point of view. You are trusted to question approaches, processes, and strategy to better serve your team and clients
• Proven experience (5+ years) in data engineering
• 5+ years of proven data engineering experience with expertise in data warehousing, data management, and data governance in SQL or NoSQL databases
• Deep understanding of data modeling, data architecture, and data integration techniques
• Advanced proficiency in ETL/ELT processes and data pipeline development from raw, structured to business/analytics layers to support BI Analytics and AI/GenAI models
• Hands-on experience with ETL tools including: Databricks (preferred), Matillion, Alteryx, or similar platforms
• Commercial experience with a major cloud platform like Microsoft Azure (e.g., Azure Data Factory, Azure Synapse, Azure Blob Storage)
• Oracle RDBMS (for OLTP): Expert SQL for complex queries, DML, DDL
• Oracle Exadata (for OLAP/Data Warehouse): Advanced SQL optimized for analytical workloads. Experience with data loading techniques and performance optimization on Exadata
• S3-Compatible Object Storage (On-Prem): Proficiency with S3 APIs for data ingest, retrieval, and management
• Python: Core language for ETL/ELT development, automation, and data manipulation
• Shell Scripting (Linux/Unix): Bash/sh for automation, file system operations, and job control
• Git: Managing all code artifacts (SQL scripts, Python code, configuration files)
• Data Pipeline Orchestration Concepts: Understanding of scheduling, dependency management, monitoring, and alerting for data pipelines
• Containerization: Docker, basic understanding of how containerization works
• API Interaction: Understanding of REST APIs for data exchange (as they might need to integrate with the Java Spring Boot microservices)

Responsibilities

• Work closely with data scientists, data architects, business analysts, and other disciplines to understand data requirements and deliver accurate data solutions
• Analyze and document existing data system processes to identify areas for improvement
• Develop detailed process maps that describe data flow and integration across systems
• Create a data catalog and document data structures across various databases and systems
• Compare data across systems to identify inconsistencies and discrepancies
• Contribute towards gap analysis and recommend solutions for standardizing data
• Recommend data governance best practices to organize and manage data assets effectively
• Propose database design standards and best practices to suit various downstream systems, applications, and business objectives