Every business on Earth must, in some way, do bookkeeping, accounting, and financial planning to operate. At the outset, these functions may seem like mundane facts-of-life in the process of running a business; however, the skill with which a company does them can have a profound impact not only on their business, but also the world. A poorly forecasted budget, could mean the abrupt end to the clinical trial of a potentially life-saving drug. On the other hand, a highly accurate hiring plan can lead to successful team growth that allows a company to design a brand-new material that helps reverse climate change.
Today, unfortunately, financial management and services are universally manual, tedious, and error prone. At the same time, these processes often follow welldefined rules, abide by industry standardization, and have become increasingly data-rich. Our team, within the Medium Segment Native Cloud Solutions at Sage, builds cloud-based AI-powered features and products that fundamentally change the way businesses operate.
We are looking for a Data Engineer to help us ship AI-powered products and services.
Responsibilities:
- Designing, implementing, and operating pipelines that deliver data with measurable quality and SLOs
- Creating tools for establishing common data management patterns across our team and beyond
- Writing production-quality code to support our data pipelines and machine learning systems
- Informing our strategy for data governance, security, privacy, quality, and retention
- Working with our AI Infrastructure team to extend our capabilities , curate new data sets, and manage the data that drives our machine learning platform
- Working with ML Engineers and data scientists to refine and specify data products that satisfy business policies and requirements
- Exploratory data analyses and investigations
Basic Qualifications:
- Bachelor's degree, preferably in a field that requires data management and manipulation (e.g. statistics, applied math, computer science, or a science field with direct statistics applications)
- Fluent in data fundamentals: SQL, data management, and data manipulation using a procedural language
- Strong quantitative and analytical skills with minimum 4 years of experience with building data-intensive applications,
- familiarity with the scientific Python toolset: numpy, scipy, sklearn, etc.
- experience with one or more workflow management technology: airflow, argo, etc.
- Experience building and operating cloud infrastructure, preferably on AWS
- Deep understanding of relational as well as big data techniques and technologies (e.g. Postgres/mysql, spark, data warehousing (s3, Redshift, Snowflake, etc.))
- Ability to work independently and deliver results on-time
- Ability to communicate complex ideas to non-technical stakeholders and alternate between big-picture and implementation.
- Excellent problem solving and critical thinking skills
Preferred Qualifications:
- Experience developing and operating machine learning pipelines with Kubeflow or Argo
- Hands-on experience with one or more ML pipeline automation frameworks - MLFlow, Kubeflow, or TFX.
- Advanced SQL skills either for DB management or analysis
- You have deep experience with these things: data warehousing, schema management, timeseries datasets, data validation, synthetic data generation, serialization protocols, data privacy and security
You may be a fit for this role if:
- You're comfortable with investigating open-ended problems and coming up with concrete approaches to solve them.
- You're a deeply curious person.
- You can wrangle data like a pro alligator wrestler and come out relatively unscathed.
- You often think about applications of machine learning in your personal life.
What it's like to work here:
You will have an opportunity to work on a small and growing team in an environment where data engineering and ML are central to our success. 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. 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 building and working with a great people.