Type: Full Time
Who we are:
We are Dataminr. We deliver real-time, actionable alerts that are derived from vast amounts of publicly available data. Our groundbreaking AI-enabled platform cuts through the noise in an increasingly complex landscape by detecting, classifying, & determining the significance of public information. Our culture promotes cross team interaction, work-life balance & the sharing of information & ideas because it enables us to do our best work & have fun. We've grown to over 450 talented employees across six global offices, raised over $570 million from leading venture & growth technology investors, & been referred to as the super tool of journalists & hedge funds.
We are a mission-driven company committed to the power of real-time information as a force for good in the world.
Who you are:
You're an experienced Data Engineer interested in working in both streaming & batch processing environments [Kafka streaming, Kinesis, Spark, SCALA, Java], writing, upgrading & scheduling ETLs that produce meaningful analytic insights for an innovative, data-intensive product. You excel at integrating data from different sources, you are intellectually curious about analytics frameworks & you are well-versed in the advantages & limitations of various big data architectures & technologies. You are also comfortable using SQL for exploratory analyses & data validation. Importantly, you understand the importance of communication in engineering & how essential it is to appreciate business metrics & business needs when building out new data analytics pipelines. You have a history of mentoring other engineers, you give your time generously & you know when to ask for help.
You will be a lead data engineer responsible for architecting & building highly-performant & maintainable analytic pipelines with the best of current technologies including both batch & streaming environments. You will write & maintain ETLs & APIs & consult with other teams on how to improve theirs. You will schedule jobs & manage workflows in support of both product & our AI/Data Science pipeline, & youll be introduced to our unique ingest & processing pipelines that turn publicly available data into breaking, real-world alerts that are routed to our customers all over the world. In the first month, youll
- start off by learning the ropes, spending time with different parts of the company to understand how Dataminr works.
- get up to speed on our data processing pipelines & data structures with overview sessions & deep dives with your team.
- contribute code to production systems.
Within 3 months, youll:
- share responsibility for ETLs & APIs with other members of your team.
- help to plan new infrastructure features & improvements.
- begin to take more of a role in helping others understand our analytics strategy.
Within 6 months, youll:
- own an area of the analytics platform.
- design & implement pipelines that impact multiple teams across the company.
- be influential in helping plan the next iteration of our analytics platform.
- bring new ideas to our engineering & analytics processes to help us continuously improve.
Why you should work here:
We recognize & reward hard work with:
- Competitive compensation package including company equity.
- Paid benefits for employees & their dependents, including medical, dental, vision, disability & life insurance
- 401 (k) savings plan with company matching.
- Flexible spending account for out-of-pocket medical, transit, parking, & dependent care expenses.
We want you to be your best, authentic self & support you with:
- A diverse, driven, & passionate team of coworkers who want you to succeed.
- Opportunities to own & drive critical projects
- Daily catered lunch
- Individual Learning & Development fund & professional training
- Generous leave & flexible hours
- Daily catered lunch & a fully stocked kitchen
- And More!
Dataminr is an equal opportunity & affirmative action employer. Individuals seeking employment at Dataminr are considered without regards to race, sex, color, creed, religion, national origin, age, disability, genetics, marital status, pregnancy, unemployment status, sexual orientation, citizenship status or veteran status.