Principal Data Engineer

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Job description

People make Sage great. From our colleagues delivering ground-breaking solutions to the customers who use them: people have helped us grow for more than thirty years, and people are driving our future as a great SaaS company. We're writing our next chapter. Be part of it!

Experience has taught us that when our customers thrive, we thrive. As a team, we always start with what customers need. Through the good… and more challenging times. Innovating at pace so customers can manage their finances, operations and people. Every one of us shapes our culture at Sage - doing what's right and succeeding together, united by our commitment to each other. We encourage each other to grow in our roles, in our careers and as individuals.

Follow us on our social media sites below to join in conversations about career tips, open positions and company news! #lifeatsage #sagecareers. All qualified applicants will be thoughtfully considered and never discriminated against based on their race, color, age, religion, sexual orientation, gender identity, national origin, disability or veteran status.

Job Description

Sage Artificial Intelligence Labs "SAIL" is a nimble team within Sage building the future of cloud business management by using artificial intelligence to turbocharge our users' productivity. The SAIL team builds capabilities to help businesses make better decisions through data-powered insights.

We are currently hiring a Principal Data Engineer to help us build machine learning solutions that will provide insights to empower businesses and help them succeed. As a part of our cross-functional team including data scientists and engineers you will help steer the direction of the entire company's Data Science and Machine Learning effort.

If you share our excitement for machine learning, value a culture of continuous improvement and learning and are excited about working with cutting edge technologies, apply today!

You have:

• 5+ years of relevant practical experience working on data integration, data modelling and metadata management

• Database experience - you know how to write and optimize SQL queries, design efficient schemas for OLAP and OLTP and understand differences and tradeoffs between them

• Expert knowledge and experience with several relevant languages, tools and frameworks: e.g. Python, SQL, Scala, Spark, Beam, Hadoop, Kafka, RabitMQ, Athena, Amazon EMR etc

• Excellent written and verbal communication skills, and ability to evaluate and explain technical details clearly

• Experience in building large scale ETL/ELT processes, datalakes and data warehouses

• Willingness to adapt to significant changes in either technology or environment

• Previous experience working with financial data is a plus

Key Responsibilities

You will:

• Work closely with our Data Scientists and ML engineers to build data warehouses and pipelines

• Collaborate with our AI Infrastructure team to extend the capabilities of our machine learning platform

• Monitor and optimize the quality and performance of our data pipelines and tools

• Collaborate with other teams to integrate new data sources, ensuring privacy and security protocols are followed

• Collaborate with data scientists and ML engineers to design and build data analytics tools for detecting data anomalies and ensuring data quality

What's it like to work here

You will have an opportunity to work in an environment where Data Science is central to what we do. The products we build are breaking new ground, and we have a focus on providing the best environment to allow you to do what you do best - solve problems, collaborate with your team and push first class software. Our distributed team is spread across multiple continents, we promote an open diverse environment, encourage contributions to open-source software and invest heavily in our staff. Our team is talented, capable and inclusive. We know that great things can only be done with great teams and look forward to continuing this direction.

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