Senior Data Platform Engineer

il y a 5 jours

Paris, Île-de-France LocalStack GmbH Temps plein

LocalStack GmbH is a dynamic, fast-growing startup headquartered in Zurich, Switzerland, with a development office in Vienna, Austria, and remote team members across the globe. We specialise in creating world-class tools to support highly efficient development and testing feedback loops for cloud application developers.

Our international customer base includes Fortune Global 500 companies, and our team of top-tier engineers and GTM experts are dedicated to becoming the leading platform for local cloud software development.

We are seeking an experienced Senior/Staff Data Platform Engineer with a proven track record of designing and building scalable data architectures, developing robust data models, and implementing data solutions that directly drive business success.

As we expand our platform's features and customer base, our data challenges and team are also growing. Our current data landscape has grown organically and consists of several key components - including our high-volume product telemetry where we're tracking some 100M+ weekly usage events from different LocalStack installations, as well as our Data Warehouse (DWH) that provides the foundation and data model for our business analytics.

We are at a critical crossroads where we need to tackle some major refactorings in the data platform to ensure our platform is ready for the next evolution of the company, including a semantic metadata layer, continuous data quality checks, systematic schema evolution, and scalable real-time data transformation pipelines.

Your role will be critical in addressing these challenges by helping to build and optimise data pipelines, automating the generation of insights from large datasets, and enabling data-driven decision-making across the organisation.

We strive to be a genuinely data-driven company, so you will be working at the heart of what will make LocalStack successful in the long run.


Data Architecture & Modelling :

Design and implement data architectures and models that support efficient storage, processing, and analysis of large datasets in an efficient and cost-effective way.


Data Pipeline Development:
Build and maintain scalable, agile, and efficient data pipelines and ETL processes to handle diverse data sources. Since the business is constantly evolving, so are the data challenges and questions that need to be answered, which means you'll need to build solutions that are flexible and able to scale both in breadth and volume.
Data Integration:

Develop solutions for integrating data from various sources, ensuring data accuracy, consistency, and availability, as well as collaborating with the core and platform teams to ingest the right data to answer critical business questions and drive strategy.


Real-Time Insights:
Utilise real-time data to drive customer observability and support proactive customer engagement.

Collaboration:

Work closely with cross-functional teams, including engineering, product management, customer success, and sales, to understand data needs and deliver solutions.


Ownership & Initiative:
We are a small and growing team, so you will be expected to proactively identify problems and opportunities in the data space, and create, drive, and implement initiatives to solve them

Hands-On Implementation:
Be ready to implement data tools and solutions, driving hands-on projects to completion

Experience:

Proven experience in building and optimising data pipelines, and strong practical familiarity with the suite of data solutions available to real business challenges.

Expertise in implementing pragmatic and scalable solutions to handle increasing data volumes, and complex and evolving business questions and needs.


Data Tools:

Strong knowledge of the suite of modern data tools and technologies, with the ability to identify the right solution for our specific business problems based on real-world experience.


Documentation Skills:
Ability to create clear and accessible documentation for data processes. We bias for results over processes, so written documentation and communication should be short, clear, and crisp, and aimed at empowering your fully remote colleagues.

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