Data Engineering Tech Lead

1 month ago

Remote Warsaw, Czech Republic Lingaro Full time
  • At least 8 years of experience as a Data Engineer, including min. 6 years of experience working with GCP cloud-based infrastructure & systems and min. 2 years in Technical Leading role.
  • Experience to lead the technical teams, collaborate with our key business stakeholders and help drive our Operations.
  • Deep knowledge of Google Cloud Platform and cloud computing services.
  • Extensive experience in design, build, and deploy data pipelines in the cloud, to ingest data from various sources like databases, APIs or streaming platforms.
  • Proficient in database management systems such as SQL (Big Query is a must), NoSQL. Candidate should be able to design, configure, and manage databases to ensure optimal performance and reliability.
  • Programming skills (SQL, Python, other scripting).
  • Proficient in data modeling techniques and database optimization. Knowledge of query optimization, indexing, and performance tuning is necessary for efficient data retrieval and processing.
  • Knowledge of at least one orchestration and scheduling tool (Airflow is a must).
  • Excellent English communication skills to effectively collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders. Ability to convey technical concepts to non-technical stakeholders in a clear and concise manner.
  • Tools knowledge: Git, Jira, Confluence, etc.
  • Experience in multinational environment and distributed teams.

Nice to have:  

  • Experience with Talend ETL tool.
  • Certifications in big data technologies or/and cloud platforms.
  • Knowledge of AecorSoft – data integrator.
  • Experience with BI solutions (e.g. Looker, Power BI, Tableau).
  • Experience with Apache Spark, especially in GCP environment.
  • 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.  
  • Great Place to Work® certified employer.
  • 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.  
  • A 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.  
  • Modern office equipment. Purchased for you or available to borrow, depending on your location.
,[You will be a part of the team accountable for design, model and development of whole GCP data ecosystem for one of our Client’s (Cloud Storage, Cloud Functions, BigQuery)., Involvement throughout the whole process starting with the gathering, analyzing, modelling, and documenting business/technical requirements will be needed. The role will include direct contact with clients. , Guiding and mentoring the data engineering team, providing technical direction, overseeing the design and implementation of data solutions, and ensuring adherence to best practices and quality standards in data engineering projects. Train and mentor less experienced data engineers, providing guidance and knowledge transfer. , Modelling the data from various sources and technologies. Troubleshooting and supporting the most complex and high impact problems, to deliver new features and functionalities. , Designing and optimizing data storage architectures, including data lakes, data warehouses, or distributed file systems. Implementing techniques like partitioning, compression, or indexing to optimize data storage and retrieval. Identifying and resolving bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency. , Identifying and resolving issues related to data processing, storage, or infrastructure. Monitoring system performance, identifying anomalies, and conducting root cause analysis to ensure smooth and uninterrupted data operations. ] Requirements: GCP, Airflow, SQL, BigQuery, Python, Talend ETL, Apache Spark, Tableau, Power BI Additionally: Sport subscription, Training budget, Private healthcare, Flat structure, Small teams, International projects.

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