Data Engineer
hace 6 meses
Our clients are ambitious, high-impact CEOs, founders, and execs. They have started 100+ companies, raised billions in venture capital, taken companies public, worked in the White House, invested in Facebook / Uber / Airbnb, run professional sports teams, are Governors of US states, and compete in Ironman races and the World Series of Poker.
They have joined Athena to get more leverage, more impact, more success, and more time via their relationship with their top 1% of Philippines-based Executive Assistants. They are world-class humans who want to get world-class at delegation.
As part of the data engineering team, you will be creating internal services for Athena employees, delivering them accessible data to power decision-making.
We are building a global team with a remote-first culture, so being able to work independently and collaborate effectively is a must.
**High-level Responsibilities**
- Create and maintain optimal, company-wide data pipeline architecture
- Assemble large, complex data sets that meet functional / non-functional business requirements
- Identify, design, and implement internal process improvements, including: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python, SQL, etc.
- Build analytics tools that use the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other business KPIs
- Work with the Executive, Product, Operations, and Design teams to assist with data-related technical & infrastructure needs
**Specific Responsibilities**
The Data Engineer will support our data analysts, data operations associates, database architects, and various business teams on data initiatives, and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
Some of the things you will work on:
- Build data pipelines that clean, transform, and aggregate disparate data
- Use software development principles to improve our back-end systems
- Model front
- & back-end data sources to draw a comprehensive picture of data flow throughout the organization and enable powerful data analysis
- Develop models that can be used to answer questions for the business
- Communicate with other teams to understand their data needs
**Your Metrics**
- Uptime for data dashboards
- Response time for data dashboards
- Internal user satisfaction with data services
**About You**
To be successful you will need a combination of problem-solving, technical, and communication skills. The following qualifications are important success factors:
- Degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field, or related experience:
- Experience with ETL tools (e.g., Fivetran, dbt, etc.)
- Experience with relational SQL and NoSQL databases, (e.g., PostgreSQL, Airtable, etc.)
- Experience with data pipeline and workflow management tools(e.g., Airflow, Luigi, Azkaban, etc.)
- Experience with GCP cloud services(e.g., BigQuery, Cloud Composer, Cloud SQL for PostgreSQL, etc.)
- Experience with object-oriented/object function scripting languages (e.g, Python, Java, etc.) & querying languages (e.g., SQL, etc.)
- Experience performing root cause analysis on data & processes to answer business questions and identify opportunities for improvement
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management
- Strong analytic skills related to working with structured & unstructured datasets
- A successful history of manipulating, processing, and extracting value from large, disconnected data systems
- Strong project management and organizational skills
- Experience supporting and working with cross-functional teams
- Great problem-solving and communication skills
- Ambitious, quick to learn, and takes ownership
- Be an advocate for best practices and continued learning
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