Staff Data Engineer

Fuldtid

Permanent

Østergade 55, 1100 København K, Danmark

SE PÅ KORT

ID: 2667353

Indrykket for 58 dage siden

Do you want to build enterprise-ready data platform solutions and assets at scale using cutting-edge technology?

Join us and be part of improving and growing our data platform assets in a fun-loving, collaborative, and international team where we explore and innovate to dive into a vast range of new opportunities.

“You’ll become one of the leading minds behind ECCO’s future analytics data ecosystem, making your mark on data engineering and enabling business units to make data-driven decisions, power analytics, and AI use-cases” says Head of Data & AI, René Matzen.

Step into our Data & AI tech hub
Here, you will join us in enabling and developing ECCO’s data initiatives and solutions. As a part of the Data Technology & Engineering team, you will gain 9 colleagues and together we work on our enterprise data platform initiatives and capabilities to improve how ECCO operates based on data.

Be the face of data engineering
As our new Staff Data Engineer, you will set and implement the technical strategy for ECCO’s enterprise data platform and its assets. Your responsibilities include representing data engineering in ECCO and public communications. This entails acting as a consultant and a thought partner to

stakeholders, including executive, Data & AI, and business line teams, and being a spokesperson for your team’s work.

Setting and implementing long-term goals and standards for enterprise ready data assets and solutions in our data platform, you will:

Offer expert advice and contribute to the development, implementation, and operation of scalable and dependable data solutions.

Create and implement structured pathways, designing data architecture, data and metadata modelling, integrating data sources, transforming data (using ETL/ELT processes), and constructing models for the semantic layer

Ship large features and foundational improvements for data solutions

Develop and implement DataOps and Data Observability principles to maintain high data quality, integrity, reliability, and security

Collaborate across product, platform, and engineering teams to continuously improve our data assets and solutions

A place to learn and influence our goals
Your new team is a part of our AI organization, which is steadily changing the way we work in ECCO. So, plenty of new initiatives are taking their first steps, which creates a great environment for learning, influencing long-term goals, and defining internal standards for a high-scale and high-reliable data platform.

Creative, collaborative, and a solid technical toolbox
In this role, you must be able to work in teams and mentor colleagues to develop the best solutions. But you can also ship large features with minimal supervision and set overall directions across core disciplines in our data life cycle.

When situations arise, you use your creative and methodical mindset to find opportunities for improving data engineering processes and test the effectiveness of different implementations and courses of action. Finally, we imagine that you:

Hold a master’s degree or PhD within science and engineering, e.g. computer science, software engineering, or electrical engineering

Have senior-level experience using Python, Java, and/or Scala

Demonstrate a deep understanding of SQL and its use in large-scale analytics unified engines (e.g. Apache Spark)

Have hands-on experience in analytical data warehousing (e.g. Snowflake) as well as with data pipeline tools (e.g. Apache Airflow) and data build tools (e.g. dbt)

Demonstrate solid data and metadata modelling skills and familiarity with standard frameworks, such as Kimball Lifecycle Methodology

Have experience using DataOps and Data Observability principles in practice and operations

Are fluent in English

Are you ready for your next challenge?
Application deadline is August 10, 2024. We plan to have first calls with candidates in second half of August.

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