Principal Data Engineer

Atlanta, United States

Invesco

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As one of the world’s leading asset managers, Invesco is dedicated to helping investors worldwide achieve their financial objectives. By delivering the combined power of our distinctive investment management capabilities, we provide a wide range of investment strategies and vehicles to our clients around the world.

If you're looking for challenging work, smart colleagues, and a global employer with a social conscience, come explore your potential at Invesco. Make a difference every day!

Job Description

Your Team
The SIP (Strategy Innovation & Planning) team is focused on building AI solutions and progressing innovation across our firm. Currently we are working on building and maintaining IVYGPT platform and working on onboarding Agentic framework to Invesco. We are working on business sponsored GenAI use cases to bring operational efficiencies into our firm. We are also heavily involved in progressing Generative AI across Invesco with AIML MeetUps, hackathons and collaborations with different teams.

Your Role

As a Principal Data Engineer, you will be expected to ideate and partner with data scientists to build solutions and products that move the needle for Invesco. You’ll be expected to tinker and experiment with the latest tools and technologies to introduce leading edge products and services to market, as well as foster new ways of working. You’ll be expected to leverage your knowledge of data and cloud to onboard, prepare, process, automate structured or unstructured data in cloud for the data scientists to build models. This position will be well-suited for someone who likes to tinker with new tools, technologies, who values speed and innovation. 

You Will Be Responsible For:

  • Collaborate with data scientists and investors to build innovative machine learning based tools using structured and alternate data sources.
  • Research, identify, extract, transform and load both unstructured and structured data to allow efficient analytics and modeling.
  • Create end-to-end data pipelines on AWS using variety of AWS services including SageMaker
  • Collaborate with the teams to build Generative AI solutions and frameworks for Azure OpenAI
  • Create production ready data workflows including automations, CI/CD pipelines and ensure data quality and availability
  • Perform ad-hoc analysis and present results in a clear manner, researching and selecting any new Big Data tools, technologies or frameworks required to provide requested capabilities
  • Guide and mentor other data engineers throughout the implementation process.
  • Participate in trial/assessment/purchase of new datasets for ML use cases


The Experience You Bring:

  • 8+ years of proven experience with data development, workflows, and data analytics
  • 8+ years of database experience with SQL server, Oracle, PostgreSQL etc.
  • 5+ experience with Amazon cloud (AWS) services such as Athena, EFS, RDS, S3, KMS, EC2, AWS Batch, EMR clusters, CloudWatch, Amazon glue etc.
  • 3+ years of programming experience (Python or Java or Scala)
  • 2+ years of experience in Apache Spark or other bigdata frameworks
  • Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, DynamoDB 
  • Advanced experience with Python, libraries, docker containers, lambda, Linux environment, and CI/CD tools such as Jenkins, BitBucket etc.
  • Exposure to microservice architecture a plus
  • Exposure to Snowflake, AWS data wrangler, SageMaker, SageMaker Studio a big plus
  • Asset management industry experience a plus
  • Agile (Scrum) experience a plus

Full Time / Part Time

Full time

Worker Type

Employee

Job Exempt (Yes / No)

Yes

Workplace Model

At Invesco, our workplace model supports our culture and meets the needs of our clients while providing flexibility our employees value. As a full-time employee, compliance with the workplace policy means working with your direct manager to create a schedule where you will work in your designated office at least three days a week, with two days working outside an Invesco office. 

What’s in it for you?

 

Our people are at the very core of our success. Invesco employees get more out of life through our comprehensive compensation and benefit offerings including: 

  • Flexible paid time off

  • Hybrid work schedule 

  • 401(K) matching of 100% up to the first 6% with a discretionary supplemental contribution 

  • Health & wellbeing benefits 

  • Parental Leave benefits 

  • Employee stock purchase plan

The above information on this description has been designed to indicate the general nature and level of work performed by employees within this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to this job. The job holder may be required to perform other duties as deemed appropriate by their manager from time to time.

Invesco's culture of inclusivity and its commitment to diversity in the workplace are demonstrated through our people practices. We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender, gender identity, sexual orientation, marital status, national origin, citizenship status, disability, age, or veteran status. Our equal opportunity employment efforts comply with all applicable U.S. state and federal laws governing non-discrimination in employment.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Engineering Jobs

Tags: Agile Architecture Athena AWS AWS Glue Azure Big Data Bitbucket Cassandra CI/CD Data Analytics Data pipelines Data quality Docker DynamoDB EC2 Generative AI HBase Java Jenkins Lambda Linux Machine Learning MongoDB NoSQL OpenAI Oracle Pipelines PostgreSQL Python Research SageMaker Scala Scrum Snowflake Spark SQL Unstructured data

Perks/benefits: Career development Equity / stock options Flex hours Flex vacation Health care Parental leave

Region: North America
Country: United States

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