AmplemarketSpontaneous Application - Data Engineer
Amplemarket is hiring a Spontaneous Application - Data Engineer for a remote role. Level rates it ; you can apply on Amplemarket.
Level's read on this job
- Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
- This is listed as a remote role.
- The posting mentions Databricks and NLP among its tools and skills.
- Level classes it as a mid-level role.
- Amplemarket has 16 other open roles on Level.
AI in this role
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- We will never request personal financial information (such as bank account details) during the initial application or interview process.
- Our hiring process does not involve transferring money or making payments of any kind to secure a position.
Amplemarket is not responsible for any loss or damage incurred as a result of job scams or fraudulent activity by third parties misusing our company name.
If you have any doubts about the legitimacy of a job opportunity with Amplemarket, please contact our HR department directly.
We advise you to verify the authenticity of any job-related communications claiming to be from Amplemarket. If you have any concerns or doubts, please contact us directly through our official channels.
Your security is our priority. Thank you for your vigilance and understanding.
Are you up for a challenge? Amplemarket welcomes spontaneous applications from talented people who are eager to join our team.
We are always on the lookout for exceptional Data Engineers who want to revolutionize the future of sales, while thriving in an incredible Engineering environment.
While we may not be prioritizing this opening at the moment - and, therefore, might take a bit longer to get back to you - we review spontaneous applications regularly and if your profile stands out, we’ll definitely want to get to know you 🙂
About the Engineering Team
The three co-founders have an engineering background (João, Luís and Mica studied Physics & Computer Science in university) and deeply value the work that engineers are responsible for.
Our main goal is to build a sales platform that helps companies grow. Our product requires us to solve a myriad of difficult engineering problems very diverse in nature: from working on NLP models that can extract information from a thread of emails to scaling an Elasticsearch cluster holding terabytes of data.
We are deeply aware of the importance of our tool to our customers and look for people that share that vision.
In this role, you will be responsible for designing, building, and maintaining the infrastructure and processes necessary for the collection, storage, and analysis of large datasets. You will work closely with our development, product, and data teams to ensure that our data is accurate, reliable, and accessible to support business decision-making, machine learning models, and drive product innovation.
You will:- Design and implement data pipelines for the collection, storage, and transformation of data from a variety of sources
- Develop and maintain data models and schema to support data analysis and reporting
- Write and maintain ETL jobs to extract, transform, and load data into our data warehouse
- Collaborate with ML engineers, data analysts, and other stakeholders to understand data requirements and develop solutions to support data-driven decision-making
- Monitor and optimize data pipelines and processes to ensure data quality and performance
About you:
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field
- 3+ years of experience as a Data Engineer or similar role
- Strong programming skills in Python, Java, or a similar language
- Experience with SQL and data modeling concepts
- Experience with cloud-based data warehousing solutions such as Redshift, BigQuery, or similar
- Experience with ETL tools such as Spark, Flink, Databricks, Snowflake, etc.
- Experience with messaging systems such as RabbitMQ, Kafka, etc.
- Knowledge of the underlying cloud infrastructure on how the various data pipeline component fit together
- Excellent problem-solving and communication skills
- Based somewhere between the GMT-3 and GMT+2 timezones
Some more about Amplemarket:
- We are a post-Series A start-up
- Backed by YCombinator
- Strong technical founding team from MIT and IST (also founders of https://fermatslibrary.com/)
- Fast growing startup with product market fit
- Great team spirit
- Nice work environment
- Competitive Salary
- Health Insurance
- Stock Options
- Annual Company Trip in a secret location
- and more
Amplemarket is committed to creating an inclusive employee experience for all. Regardless of race, gender, religion, sexual orientation, age, disability, or if you’re parenting the next generation of innovators, we firmly believe that what truly matters is how your skills, knowledge and personality fit our company. So bring your best professional version of yourself, and apply - we'd like to hear from you!
How we rate this
Spontaneous Application - Data Engineer at Amplemarket rates 21 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical data engineer job
- $146k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: NLP and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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