Data Engineering Tech Lead

About Lingaro:

Lingaro Group is the end-to-end data services partner to global brands and enterprises. We lead our clients through their data journey, from strategy through development to operations and adoption, helping them to realize the full value of their data.

Since 2008, Lingaro has been recognized by clients and global research and advisory firms for innovation, technology excellence, and the consistent delivery of highest-quality data services. Our commitment to data excellence has created an environment that attracts the brightest global data talent to our team.

About Data Engineering :

Data engineering involves the development of solutions for the collection, transformation, storage and management of data to support data-driven decision making and enable efficient data analysis by end users. It focuses on the technical aspects of data processing, integration, and delivery to ensure that data is accurate, reliable, and accessible in a timely manner. It also focuses on the scalability, cost-effectiveness, security, and supportability of the solution. Data engineering encompasses multiple toolsets and architectural concepts across on-premises and cloud stacks, including but not limited to data warehousing, data lakes, lake house, data mesh, and includes extraction, ingestion, and synchronization of structured and unstructured data across the data ecosystem. It also includes processing organization and orchestration, as well as performance optimization of data processing.

Job Requirements:

At least 6 years of experience as a Data Engineer, including min. 4 years of experience working with GCP cloud-based infrastructure & systems and min. 2 years in Technical Leading role.
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).
Experience with data integration tools and techniques, such as ETL and ELT Candidate should be able to integrate data from multiple sources and transform it into a format that is suitable for analysis.
Excellent 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.
Ability to actively participate/lead discussions with clients to identify and assess concrete and ambitious avenues for improvement.
Tools knowledge: Git, Jira, Confluence, etc.
Open to learn new technologies and solutions.
Experience in multinational environment and distributed teams.

Tasks :

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.

Nice to have:

Certifications in big data technologies or/and cloud platforms.
Experience with BI solutions (e.g. Looker, Power BI, Tableau).
Experience with ETL tools: e.g. Talend, Alteryx
Experience with Apache Spark, especially in GCP environment.
Experience with Databricks.
Experience with Azure cloud-based infrastructure & systems.

`We Offer:`

Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
100% remote.
Flexibility regarding working hours.
Full-time position
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.