Big Data Specialist

Key Skills

Apache Airflow, AWS, Big Data Technology, Data Analytics, Data Architecture, Data Modeling, Data science techniques, Google Cloud Platform (GCP), Planning and organization, SQL

Job Description

We are looking for our next Big Data Specialist or Analytics Engineer Specialist to be part of the Big Data team where they design, create, maintain the data model for the exploitation of the different businesses and have a long-term view, working hand in hand with the Area Manager.

Design and empower your team on data modeling topics on a consumable data set for technical purposes and non-technical stakeholders. Create, maintain and implement data products for Analytics & DataViz and AI & Machine Learning teams on Cloud Platforms, preferably in GCP , and/or AWS .

At Xepelin we are creating a new standard of financial services, which brings many challenges of scale and implementation, so we need your creativity, leadership and talent.

We like to work in an environment where you can freely express your ideas and have the collaboration of all the teams. We have the confidence to say things upfront and we care about maintaining long-term relationships.

You will have the opportunity to...

• Be a key player in prioritizing work within the team; doing so effectively to generate value and impact in the organization and being able to measure and understand the risks associated with decisions.
• Mentor and be able to provide not only a technical, but also a strategic vision when implementing Data products.
• Have a practical/advanced knowledge of implementation technologies, designed and structured pipelines as simple and reproducible as possible.
• Design, create and maintain the source of truth and build the semantic layer to be used by all of Xepelin.
• Have a critical look at issues of how to maintain and optimize the data modeling necessary to understand the different business units, as well as to be consumed by the other data teams.
• Design and build automated data workflows, such as data ingestion, aggregation, and ETL or ELT processing.
• Design and empower your team on data modeling issues, raw data quality in data warehouses in a consumable data set for technical purposes and non-technical stakeholders.
• Create, maintain and deploy data products for data science and analytics teams on Cloud Platforms, preferably GCP, and/or AWS.
• Have knowledge of orchestration tools, address transformation models and coordination with the team.
• Establish new modeling and consumption best practices that will benefit the business.
• Being a standard of quality and development cycles of data products, as well as promoting the use and creation of documentation and tools that allow the work developed by the team to be shown.

What will help you succeed?

• Knowledge of some Cloud, preferably GCP or AWS (in that order of preference).
• Advanced knowledge of SQL.
• Advanced knowledge of data modeling techniques.
• Intermediate/advanced knowledge in data ingestion and pipeline orchestration.
• Intermediate/advanced knowledge of Python.
• Experience working cloud storage such as GCS
• Having led teams in the past. Be humble and know how to collaborate. Be a Team Player, not just a team leader.
• Know how to listen to your stakeholders and be able to translate that into requirements and execute them with your team.
• Proactive and responsible work. Have good communication and diction.

What will catch our attention...

• Knowledge of DBT.
• Experience in an orchestrator, for example: Dagster, Apache Airflow, Prefect, etc.
• Don't be afraid to make decisions and lead projects.
• Focus on impact and consistent history delivering results for users and the business.
• Ability to think big and develop initiatives with real and measurable impact.
• You are comfortable challenging the status-quo of financial services, adapting quickly to changes, and clearly presenting your ideas and concepts for team discussion.