Data Engineer

• Creating and maintaining the most appropriate data pipeline architecture and improve its scalability, efficiency and cost-effectiveness;
• Monitoring and resolving data pipeline problems that will guarantee consistency and availability of the data;
• Ensuring consistent standards and quality in the data platform ecosystem, implementing data validation and cleansing procedures that will ensure the quality, integrity, and dependability of the data;
• Assembling large, complex data sets that meet functional / non-functional business requirements;
• Identifying, design, and implementing internal process improvements: automate existing manual processes, optimize data delivery, re-design infrastructure for greater scalability, etc.;
• Building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources;
• Helping to build analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics;
• Partnering with the product managers, engineers, and other internal teams, to assist with data-related decisions and support their data infrastructure needs.

• At least 2 years of experience in a Data Engineering role;
• Experience building and optimizing ‘big data’ pipelines, architectures, and data sets;
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement;
• Analytical skills related to working with unstructured datasets;
• Hands-on experience with processes supporting data transformation, data structures, metadata, dependency management, and workload management;
• A successful history of manipulating, processing, and extracting value from large disconnected datasets.

You also have familiarity with:

• Cloud platform Azure: utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations.
• SQL and NoSQL databases (e.g. SQL Server, PostgreSQL, MongoDB), as well as professional-acquired familiarity with a variety of databases, are a plus;
• It is nice to have experience with Python/C#;
• Custom ETL design, implementation, and maintenance;
• It is nice to have knowledge of Google BigQuery, Looker Studio or any other data representation tool such as Power BI.

• Excellent problem-solving skills;
• Strong attention to detail;
• Ability to work independently or collaboratively in a fast-paced environment;
• Proven experience working within an Agile environment;
• Strong communication and interpersonal skills to effectively collaborate with cross-functional teams.