Investing.com, a leading global financial news and data platform, is looking for a Head of Data Engineering to join our Data team and play a key role in advancing our data platform and engineering capabilities.
This is a senior individual contributor role with broad impact across the organization. You'll combine deep technical expertise with strategic thinking to establish best practices, introduce modern methodologies and technologies, and help shape the future of data engineering at Investing.com.
Partnering with stakeholders across the organization, you'll build scalable data solutions, drive data quality and integrity, and identify opportunities to leverage AI to make our data platform smarter, more efficient, and more impactful.
Investing.com is a leading financial platform that helps retail investors and traders find opportunities others can't. 50 million investors rely on us every month, tracking 180,000 instruments across 250 exchanges, in 33 languages. More than 300,000 subscribe to our premium tools: AI-powered stock picks, Vision AI chart analysis, a personal AI research assistant, Fair Value assessments, and breaking news - getting institutional-level intelligence without the institutional-level fees.
We're a global team of 250+ people who've been raising the bar on what's possible for everyday investors since 2007. And we're just getting started.
What we offer:
A seat at one of the world's top financial platforms - building products that millions actually use
Work that matters locally and globally
A high-energy environment with real benefits to match
Who thrives here:
Self-starters who are curious, resourceful, and sharp. People who take ownership, move fast, and collaborate well.
Sound like you? Check out open roles at https://www.investing-careers.com/
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Drive data governance, data quality, integrity, and engineering best practices.
Introduce methodologies, tools, and standards that improve scalability, maintainability, and productivity.
Improve data engineering processes, documentation, and workflows.
Leverage AI & Innovation
Identify opportunities where AI can improve data engineering workflows and operational efficiency.
Explore, experiment with, and implement AI-powered solutions that address real engineering and business challenges.
Collaborate & Deliver
Partner with analysts, engineers, and stakeholders to deliver trusted, high-quality data solutions.
Translate business needs into scalable technical solutions.
Build strong relationships with stakeholders by ensuring reliable and accessible data.
Build Scalable Data Solutions
Design, develop, and maintain end-to-end ETL pipelines, from business requirements through implementation.
Develop scalable data models and optimize data warehouses for performance and reliability.
Build and support complex data workflows using Python, BigQuery, Apache Airflow, and cloud technologies.
Develop and maintain monitoring solutions to ensure the reliability and quality of data pipelines.
What You'll Bring
Technical Experience
8+ years of experience in Data Engineering.
Strong experience with Python, SQL, BigQuery (or similar analytical databases), and Apache Airflow.
Deep understanding of data modeling, ETL design, and cloud-based data platforms (GCP preferred).
Experience designing complex business workflows and data processes.
Experience with Tableau infrastructure.
Familiarity with streaming data frameworks (Kafka, Pub/Sub).
Data Engineering Leadership
Strong understanding of data governance, data quality, and engineering best practices.
Experience introducing new technologies, methodologies, or standards.
Ability to influence technical direction and improve how data engineering teams operate.
Strong stakeholder management skills, with the ability to build trust, align expectations, and drive collaboration across technical and business teams.
Ability to translate complex technical topics into clear recommendations and drive initiatives forward.
AI Mindset
Experience using AI tools to improve engineering workflows and productivity.
Curiosity and initiative to explore AI technologies and apply them to solve real engineering problems.
Ability to identify opportunities where AI can create value and turn ideas into practical solutions.