Data Engineer III

Astreya; San Francisco (CA); On-site; USD 110,000 - 130,000; Full time

Job summary

Astreya is seeking a Data Engineer to join our analytics team. The hire will expand and optimize data and data pipeline architecture, and improve data flow for cross functional teams.

The Data Engineer will support analysts on data initiatives, ensure scalable infrastructure for ongoing projects, and collaborate with Product, Data and Design to deliver actionable insights.

Initial contract with a strong likelihood of converting to a permanent position (~4-5 months out).

Qualifications

• Bachelor’s degree and 5–8 years of related experience.
• Networks with senior internal and external personnel in own area of expertise.
• Proficiency in SAS, Python, Java, and MatLab.
• ETL, Database – SQL and NoSQL.
• Data Warehousing – Hadoop, MapReduce, Hive, Presto.

Responsibilities

• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets meeting business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for scalability.
• Build infrastructure for ETL of data from diverse sources.
• Develop analytics tools that leverage the data pipeline to provide actionable insights.
• Collaborate with executives, product, data and design teams to support data infrastructure needs.
• Create data tools for team members to assist in analytics production.

Skills

SAS

Python

Java

MatLab

Education

Bachelor’s degree (B.S./B.A.)

Tools

ETL

SQL

NoSQL

Hadoop

MapReduce

Hive

Presto

Job description

Contract Type: Initial contract with a strong likelihood of converting to a permanent position (~4-5 months out)

What this Job Entails:

We are looking for a Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The Data Engineer will support our data analysts on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.

Scope:

• Resolves a wide range of issues in creative ways
• Seasoned, experienced professional with a full understanding of their specialty
• Works on problems of a diverse scope
• Receives little instruction on day to day work, general instruction on new assignments

Your Roles and Responsibilities:

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: 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
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for team members to assist them in building and optimizing analytics production.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Other duties as required. This list is not meant to be a comprehensive inventory of all responsibilities assigned to this position

Required Qualifications/Skills:

• Bachelor’s degree (B.S/B.A) from four-college or university and 5 to 8 years’ related experience and/or training; or equivalent combination of education and experience
• Networks with senior internal and external personnel in own area of expertise
• Demonstrates good judgment in selecting methods and techniques for obtaining solutions
• Proficiency in languages SAS, Python, Java, and MatLab
• ETL (Extract, Transform, and Load)
• Database - SQL and NoSQL
• Data Warehousing – Hadoop, MapReduce, HIVE, Presto
• Follows standard practice and procedures when analyzing situations or data

Preferred Qualifications:

• Basic Machine Learning

Physical Demand & Work Environment:

• Must have the ability to perform office-related tasks which may include prolonged sitting or standing
• Must have the ability to move from place to place within an office environment
• Must be able to use a computer
• Must have the ability to communicate effectively
• Some positions may require occasional repetitive motion or movements of the wrists, hands, and/or fingers