Senior Data Engineer

ETFBOOK; United States; Remote; USD 100,000 - 156,000; Full time

Benefits offered by this job

Remote work across Europe timezone

Competitive B2B contract

Growth opportunities in a fast-paced I

Impactful ETF data projects

Real-world product development impact

Culture of innovation

Biannual team-building events

Job summary

ETFBOOK is seeking an experienced Data Engineer to design and maintain robust data pipelines on Azure-based Databricks. You will help define the data model and deliver trusted datasets to clients, reporting to the Lead Data Engineer in a collaborative tech team.

You will contribute to end-to-end data delivery, collaborate with analytics, data science, and product teams, and mentor junior engineers while focusing on security, performance, and cost optimization.

Qualifications

• 8+ years of professional experience in Data Engineering.
• Experience with Spark, Databricks, dbt, Snowflake or similar.
• 8+ years programming in Python, Java/Scala, or C#.
• Experience with big data storage like Delta Lake, Iceberg, HDFS.
• Knowledge of data governance, security and performance optimization.
• Strong communication and stakeholder management.
• Experience leading cross-functional projects.
• Ability to mentor junior engineers.
• Ability to provide technical leadership and work independently.

Responsibilities

• Leads complex data engineering projects and pipeline development.
• Designs scalable, secure, and high-performance data architecture.
• Defines engineering standards and best practices for data pipelines.
• Works closely with Data Analytics, Data Science, Product, and the whole rest of engineering teams.
• Mentor junior engineers and provides technical guidance.
• Drives improvements in performance, reliability, security, and cost optimization of the data platform.

Skills

Data engineering

Spark/Databricks

Programming languages (Python/Java/SC/

Big data storage

Data governance

Security & performance

Cross-functional leadership

Mentoring

Stakeholder management

Tools

Databricks

dbt

Snowflake

Delta Lake

Iceberg

HDFS

Job description

Location: Remote (European Time Zone), once per month in the office in Cracow

Contract Type: B2B

About us:

ETFBOOK is a Swiss SaaS company providing data, analytics, and custom solutions in the Exchange Traded Funds (ETFs) space. Founded in 2020, we aim to make global ETF data accessible, actionable, and valuable for institutional participants, including ETF issuers, index providers, fund service providers, market makers, exchanges, and buy-side institutions.

We develop a platform which offers comprehensive insights through a user-friendly web application and robust APIs, covering areas such as product analysis, fund flow tracking, performance comparisons, and liquidity assessments.

About the role:

You will work in an environment where data is a main product, not a side reporting function.

You’ll join a highly skilled data engineering team, part of a technology department. This team develops and maintains data pipelines on Azure using Databricks to support all core business functions. Your primary goal will be building and maintaining robust, secure data pipelines and helping in defining the data model that delivers trusted datasets to our clients.

Reporting to Lead Data Engineer, you’ll participate in a collaborative cross-functional team consisting of engineers, data analysts and product owners capable to deliver end to end solutions – from data acquisition to end client delivery. This role offers the chance to make a visible impact in a dynamic, fast-evolving field.

Responsibilities:

• Leads complex data engineering projects and pipeline development.
• Designs scalable, secure, and high-performance data architecture.
• Defines engineering standards and best practices for data pipelines.
• Works closely with Data Analytics, Data Science, Product, and the whole rest of engineering teams.
• Mentor junior engineers and provides technical guidance.
• Drives improvements in performance, reliability, security, and cost optimization of the data platform.

Requirements:

• 8+ years of professional experience in Data Engineering.
• Excellent knowledge of one or more data processing and analytics frameworks, such as Apache Spark, Databricks, dbt, Snowflake, or similar technologies.
• 8+ years of professional experience with an object-oriented or functional programming language, such as Python, Java/Scala, or C#.
• Strong knowledge of big data and distributed storage technologies, such as Delta Lake, Apache Iceberg, HDFS, or similar platforms.
• Strong understanding of data governance, security, and performance optimization.
• Strong communication and stakeholder management skills.
• Experience leading cross-functional projects.
• Ability to mentor junior engineers.
• Ability to provide technical leadership and work independently.

Nice to have:

• Experience with ETF (Exchange-Traded Fund) data or financial data products is highly appreciated.
• Experience applying data modelling and data architecture concepts, including database normalization, dimensional modelling (star schema), and/or Data Vault modelling.
• Experience implementing code quality, data quality, and automated testing practices, using tools such as Great Expectations (GX), dbt Tests, Deequ/PyDeequ, or similar frameworks.
• Familiarity with data platform architecture, data governance best practices, security principles, and data observability.

What we offer:

• 100% remote work from anywhere within the European time zone.
• Competitive B2B contract.
• Exciting growth opportunities in a fast-paced startup.
• Impactful work: help revolutionize ETF data market, currently fastest growing area of finance.
• Have a real impact of developing products: your work will directly influence live projects, delivering measurable results in real-world applications.
• Culture of innovation: collaborate with forward-thinking professionals in technology and finance where experimentation and creativity are encouraged.
• Team- buildings events at least twice a year, hosted in various European locations.