Data Engineering Architect

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
  • Bachelor’s degree in Computer Science, Information Technology, or a related field. A Master’s degree may be preferred.
  • 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.
We offer:
  • Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites.
  • “Office as an option” model. You can choose to work remotely or in the office. 
  • Flexibility regarding working hours and your preferred form of contract.
  • Comprehensive online onboarding program with a “Buddy” from day 1.   
  • Cooperation with top-tier engineers and experts. 
  • Unlimited access to the Udemy learning platform from day 1.
  • Certificate training programs. Lingarians earn 500+ technology certificates yearly. 
  • Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
  • Grow as we grow as a company. 76% of our managers are internal promotions.
  • diverse, inclusive, and values-driven community.   
  • Autonomy to choose the way you work. We trust your ideas. 
  • Create our community together. Refer your friends to receive bonuses.
  • Activities to support your well-being and health.
  • Plenty of opportunities to donate to charities and support the environment.