Azure Data Engineering Architect - freelance

Lever, Inc.; Polska; On-site; PLN 180,000 - 240,000; Full time

Job summary

Lever, Inc. in Poland is seeking a Data Engineering Architect to design and oversee scalable data architectures, ensuring performance, security, and maintainability across the stack.

You will define data models, ETL pipelines, and data governance practices, collaborating with data scientists, analysts, and stakeholders to enable reliable analytics and reporting while aligning with the company's long-term data strategy.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or related field.
• Master's degree may be preferred.
• Strong understanding of data modeling, ETL, data pipelines, and data governance.
• Experience with designing scalable data processing frameworks.
• Experience with relational and NoSQL databases, data lakes, and data warehouses.
• Proficiency in Python, PySpark, SQL.
• Experience with cloud platforms (AWS, GCP, Azure).
• Excellent communication and leadership skills.

Responsibilities

• Collaborate with stakeholders to understand requirements and translate into data engineering solutions.
• Design and oversee data architecture and infrastructure for scalability, performance, security, and maintainability.
• Define data models and schemas to meet business needs.
• Select and integrate data technologies to support processing and analysis.
• Create scalable ETL processes, data pipelines, and integration solutions.
• Ensure data solutions align with long-term data strategy and governance practices.
• Collaborate with data scientists and analysts to enable effective data analysis and reporting.
• Provide technical guidance and mentorship to data engineering teams.

Skills

Python

PySpark

SQL

Stakeholder communication

Leadership

Agile experience

Analytical thinking

Cloud platforms

Education

Bachelor's degree in Computer Science / Information Technology

Master's degree preferred

Tools

Relational databases

NoSQL databases

Data lakes

Data warehouses

Hadoop

Spark

AWS

GCP

Azure

Job description

Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics.

Tasks

• Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions.

• Design and oversee the overall data architecture and infrastructure, ensuring scalability, performance, security, maintainability, and adherence to industry best practices.

• Define data models and data schemas to meet business needs, considering factors such as data volume, velocity, variety, and veracity.

• Select and integrate appropriate data technologies and tools, such as databases, data lakes, data warehouses, and big data frameworks, to support data processing and analysis.

• Create scalable and efficient data processing frameworks, including ETL (Extract, Transform, Load) processes, data pipelines, and data integration solutions.

• Ensure that data engineering solutions align with the organization's long-term data strategy and goals.

• Evaluate and recommend data governance strategies and practices, including data privacy, security, and compliance measures.

• Collaborate with data scientists, analysts, and other stakeholders to define data requirements and enable effective data analysis and reporting.

• Provide technical guidance and expertise to data engineering teams, promoting best practices and ensuring high-quality deliverables. Support to team throughout the implementation process, answering questions and addressing issues as they arise.

• Oversee the implementation of the solution, ensuring that it is implemented according to the design documents and technical specifications.

• Stay updated with emerging trends and technologies in data engineering, recommending and implementing innovative solutions as appropriate.

• Conduct performance analysis and optimization of data engineering systems, identifying and resolving bottlenecks and inefficiencies.

• Ensure data quality and integrity throughout the data engineering processes, implementing appropriate validation and monitoring mechanisms.

• Collaborate with cross-functional teams to integrate data engineering solutions with other systems and applications.

• Participate in project planning and estimation, providing technical insights and recommendations.

• Document data architecture, infrastructure, and design decisions, ensuring clear and up-to-date documentation for implementation, reference and knowledge sharing.

Requirements

• Proven work experience as a Data Engineering Architect or a similar role and strong experience in in the Data & Analytics area.

• Strong understanding of data engineering concepts, including data modeling, ETL processes, data pipelines, and data governance.

• Expertise in designing and implementing scalable and efficient data processing frameworks.

• In-depth knowledge of various data technologies and tools, such as relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks (e.g., Hadoop, Spark).

• Experience in selecting and integrating appropriate technologies to meet business requirements and long-term data strategy.

• Ability to work closely with stakeholders to understand business needs and translate them into data engineering solutions.

• Strong analytical and problem-solving skills, with the ability to identify and address complex data engineering challenges.

• Proficiency in Python, PySpark, SQL.

• Familiarity with cloud platforms and services, such as AWS, GCP, or Azure, and experience in designing and implementing data solutions in a cloud environment.

• Knowledge of data governance principles and best practices, including data privacy and security regulations.

• Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.

• Experience in leading and mentoring data engineering teams, providing guidance and technical expertise.

• Familiarity with agile methodologies and experience in working in agile development environments.

• Continuous learning mindset, staying updated with the latest advancements and trends in data engineering and related technologies.

• Strong project management skills, with the ability to prioritize tasks, manage timelines, and deliver high-quality results within designated deadlines.

• Strong understanding of distributed computing principles, including parallel processing, data partitioning, and fault-tolerance.

• Bachelor's degree in Computer Science, Information Technology, or a related field. A Master's degree may be preferred.

Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.