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Data Engineer (Hadoop) @ Verita HR

Summary

Builds and optimizes Hadoop/Spark-based ETL pipelines in Python for a large bank, handling raw and structured data to support analytics and BI teams.

• Prestigious position at one of the world’s largest banks
• Stable, long-term projects
• Competitive salary with a B2B contract
• Hybrid work (6 days per month from the office in Cracow) and flexible working hours
• Private healthcare and multisport card
• Personal growth and development opportunities with the possibility to rotate between projects
• Referral program and company events
• Convenient parking
• Demonstrated ability and enthusiasm in mentoring team members
• Strong stakeholder management and communication skills
• Self-mastery with a focus on positive mindsets and professional behaviours
• Maintains the highest standards of integrity and professionalism, and supports non-discriminatory, collaborative, inclusive and culturally sensitive behaviours
• Experience with industry groups and external vendors; representing domain expertise and influence
• Strong understanding of risk management and compliance through the engineering process
• Champions innovation and the adoption of advanced technologies and best practices within the domain
• Supports professional growth of engineers through coaching and mentoring • Prestigious position at one of the world’s largest banks
• Stable, long-term projects
• Competitive salary with a B2B contract
• Hybrid work (6 days per month from the office in Cracow) and flexible working hours
• Private healthcare and multisport card
• Personal growth and development opportunities with the possibility to rotate between projects
• Referral program and company events
• Convenient parking ,(Extensive enterprise experience with Hadoop, Spark and Splunk, Proficiency in data modelling and ETL pipeline design, particularly in Python, Skilled in handling raw, structured, semi-structured and unstructured data (SQL and NoSQL), Experience in the full lifecycle of data ingestion, transformation and frameworks, Strong background in building and optimising ETL/ELT data pipelines, Familiarity with source control and implementing Continuous Integration/Continuous Deployment (CI/CD) pipelines, Experience supporting and collaborating with BI and Analytics teams in fast-paced environments, Ability to deliver high-quality work under tight deadlines, Excellent analytical and problem-solving skills, Knowledge of agile methodologies such as Scrum or Kanban is a plus, Demonstrated experience in technical leadership and mentoring junior engineers, Capable of managing multiple technical projects and mentoring teams, including unit and integration tests within automated testing environments to ensure high quality, Proven ability to quickly understand and solve complex data challenges through data engineering) Requirements: Hadoop, Splunk, Spark, ETL, Python

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