Senior Data Engineer – 10263

Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in securing the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.
Assignment Description:
We are looking for a Senior Data Engineer to join our dynamic team.
What You Will Work On:
Analyze and document existing manual data collection processes, identifying opportunities for optimization and automation.
Design and implement a robust, scalable, and efficient data engineering and processing pipeline that meets the needs of the organization.
Select and deploy appropriate tools, technologies, and frameworks for data ingestion, transformation, storage, and processing.
Ensure the quality, integrity, and consistency of data throughout the pipeline, incorporating validation, error handling, and monitoring mechanisms.
Ensure that all data engineering practices comply with relevant data protection regulations (e.g., GDPR, CCPA) and internal data governance policies.
Implement data access controls, encryption, and anonymization techniques to maintain data security and privacy.
Identify and prioritize the components and tasks necessary for transitioning from manual processes to an automated pipeline.
Develop comprehensive project plans, including scope, timelines, resource requirements, and risk assessments.
Lead and manage data engineering projects to ensure on-time delivery within scope, maintaining high quality and compliance standards.
Collaborate closely with data analysts, data scientists, software engineers, and business stakeholders to ensure alignment and successful project outcomes.
Establish and maintain data quality metrics and KPIs, and implement automated data quality checks and validation processes.
Work with data stewards and business users to define and enforce data quality standards across the organization.

What You Bring:
Educational Background: Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; a Master’s degree is preferred.
Experience: 5+ years of experience in data engineering with a strong focus on data pipeline design, implementation, and optimization.
Technical Proficiency:
Expertise in programming languages such as Python.
Experience with data processing frameworks like Apache Spark and Apache Kafka.
Strong knowledge of SQL and NoSQL database systems and data warehousing solutions.
Proficiency with cloud platforms (e.g., AWS, Azure, Google Cloud) and related data services.
Data Compliance and Governance: Solid understanding of data governance, data privacy regulations, and compliance requirements.
Project Management Skills: Proven ability to manage and deliver complex data engineering projects on time and within scope.
Analytical and Problem-Solving Skills: Strong capacity to analyze, diagnose, and solve technical and process challenges.
Data Quality Expertise: Familiarity with data quality tools and best practices for maintaining high standards.