Data Engineer

PwC

Senior Data Engineer designing, building, and maintaining data pipelines for financial services at PwC. Managing end-to-end data engineering solutions and collaborating with stakeholders.

Posted 6/30/2026full-timeRemote • 🇵🇱 PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines and platforms, with a strong focus on ETL/ELT processes, data quality, and performance optimization. Proficient in collaborating with stakeholders to translate business requirements into effective technical solutions.

Highest-signal resume keywords

Data EngineeringETL/ELT DevelopmentDatabricks (Apache Spark, SQL, Python)Data ModellingCloud-Based Data Platforms (Azure)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELTData WarehousingData QualitySQLPythonDatabricks NotebooksDelta LakeData GovernanceData StructuresPerformance Optimization

Soft Skills

Excellent CommunicationCollaborationAbility to Work Under PressureMentoring

Tools & Technologies

DatabricksDelta LakeAzureSparkCollibra

Certifications & Qualifications

Master’s Degree in Computer Science, Data Engineering, Mathematics, Statistics or Similar

Industry Keywords

Financial ServicesAnti Financial CrimeRegulatory RequirementsStreaming Data Processing

Tech Stack

Tools & technologies

ApacheAzureCloudETLPandasPySparkPythonSparkSQL

About the role

Key responsibilities & impact

You will design, build and maintain scalable, reliable data pipelines and data platforms supporting analytical and reporting solutions
You will work on end-to-end data engineering solutions – from data ingestion, through transformation and storage, to serving curated datasets for analytics and reporting
You will develop and optimize ETL / ELT pipelines using Databricks (Apache Spark, SQL, Python) and Delta Lake technologies
You will be responsible for data modelling, data structures and performance optimization in analytical data stores (lakehouse / data warehouse)
You will implement and maintain data quality, data validation and monitoring mechanisms ensuring accuracy, consistency and reliability of processed data
You will collaborate closely with data analysts, BI developers and business stakeholders to translate business and regulatory requirements into robust technical solutions
You will contribute to architecture decisions related to data platforms, data processing patterns and technology choices
You will support and mentor junior data engineers, helping them grow their technical and consulting competencies
You will actively participate in client-facing work – discussing requirements, presenting solutions and explaining technical concepts in an accessible way
In addition to project work, you will keep up with latest data engineering, cloud and Anti Financial Crime trends and contribute to internal initiatives and accelerators.

Requirements

What you’ll need

Master’s degree (preferably in Computer Science, Data Engineering, Mathematics, Statistics or similar)
Commercial experience in data engineering, database development or data platform roles
Strong understanding of data engineering fundamentals: ETL/ELT, data warehousing, lakehouse architectures
Hands-on experience with Databricks, including: – building and maintaining Spark-based batch and/or streaming data pipelines, – working with Delta Lake (ACID tables, schema evolution, incremental processing, merges), – optimizing performance (partitioning, file compaction, query optimization), – developing pipelines using Databricks notebooks, jobs and workflows
Very good knowledge of SQL (designing, writing and optimizing complex queries)
Experience with Python for data processing and transformations (e.g. pandas, PySpark)
Solid understanding of data modelling, data quality and data governance concepts
Experience working with cloud-based data platforms (Azure preferred)
Ability to gather and translate business requirements into technical solutions
Excellent communication skills and ability to work with both technical and non-technical stakeholders
Ability to work effectively under pressure while maintaining a high level of accuracy
Fluent written and spoken English
Willingness to work in international project teams
Nice to have: Experience with streaming data processing (e.g. Spark Structured Streaming), Knowledge of data governance or metadata tools (e.g. Collibra), Experience in financial services, AML / AFC or regulatory-driven environments, Additional languages: German, Dutch or French

Benefits

Comp & perks

Work flexibility - hybrid working model, flexible start of the day, sabbatical leave
Development and upskilling - our full support during onboarding process, mentoring from experienced colleagues, training sessions, workshops, certification co/financed by PwC and conversations with native speaker
Wide medical and well-being program - a medical care package (incl. physiotherapy, discounts on dental care), coaching, mindfulness sessions, psychological support, education through dedicated webinars and workshops, financial and legal advice
Possibility to create your individual benefits package (a.o. lunch pass, insurance packages, concierge, veterinary package for a pet, massages) and access to a cafeteria - vouchers, discounts on IT equipment and car purchase
3 paid hours for volunteering per month
Additional paid Birthday Day off