Azure Data Engineering Architect - freelance

Lingarogroup; Poland; On-site; PLN 180,000 - 240,000; Full time

Job summary

Lingarogroup is seeking a Data Engineering Architect in Poland to lead the design and implementation of scalable data platforms. You will work with stakeholders to translate business needs into robust data solutions and guide the data engineering team through complex migrations and pipelines.

You will drive data models, governance, and cloud-based architectures (AWS/GCP/Azure) while ensuring security, quality, and alignment with long-term analytics strategy.

Qualifications

• Experience as a Data Engineering Architect or similar in Data & Analytics.
• Strong knowledge of data modeling, ETL, pipelines, and governance.
• Ability to design scalable data processing frameworks.
• Knowledge of databases, data lakes, warehouses and big data frameworks like Hadoop/Spark.
• Ability to translate business needs into data engineering solutions.
• Familiarity with cloud platforms (AWS, GCP, Azure).
• Excellent communication and leadership skills.

Responsibilities

• Collaborate with stakeholders to translate business requirements into data engineering solutions.
• Design and oversee data architecture and infrastructure for scalability, performance, security, maintainability.
• Define data models and schemas to meet business needs.
• Select and integrate data technologies (databases, data lakes, warehouses, big data frameworks).
• Create scalable ETL processes, data pipelines, and integration solutions.
• Ensure data engineering solutions align with long-term data strategy and goals.
• Evaluate data governance strategies including privacy and security measures.
• Collaborate with data scientists and analysts to enable data analysis and reporting.
• Provide technical guidance to data engineering teams and support during implementation.
• Oversee implementation per design documents and specifications.
• Stay updated with trends, recommending innovative data solutions.
• Conduct performance analysis and optimize data systems.
• Ensure data quality and integrity with validation and monitoring.
• Collaborate with cross-functional teams to integrate data with other systems.
• Participate in project planning and estimation.
• Document data architecture, infrastructure, and design decisions.

Skills

Python

PySpark

SQL

Data modeling

ETL

Data governance

Cloud platforms (AWS/GCP/Azure)

Communication

Leadership/mentoring

Education

Bachelor's degree in CS/IT or related

Master's degree preferred

Tools

Relational databases

NoSQL databases

Data lakes

Data warehouses

Big data frameworks (Hadoop, Spark)

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.

• 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.

• 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.