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Data Engineer

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 North America Client Transactions & Data team is to streamline access to Client Information. We provide predictable data that enables our partners to respond more nimbly and rapidly to our changing business environment. By centralizing and delivery of our client data as a product, we provide transparent roadmaps while using a standardized, consistent & predictable in engineering practices.

Your Role

You will be responsible for supporting advanced analytics initiatives and data integration. Interact with Business Owners, Product Owners, Business Data Analysts, and Application Developers, to design, build and manage large-scale batch and real-time data pipelines utilizing various data analytic frameworks.  The position requires a strong technical hands-on-skilled engineer.  A successful candidate must demonstrate strong analytical, design, programing, and debugging skills in a large-scale analytics solutions.


You Will Be Responsible For:
 

  • Managing application and data integration platforms using AWS Cloud Components
  • Building robust data pipeline using modern data engineering practice in a Cloud architecture
  • Understand the business and enable the full life cycle of development/ reporting/ integration projects: planning, design, develop, testing and rollout that confirms to Agile Standards
  • Responsible for Data availability /enablement for business reporting and analytics within the SLA
  • Create and manage data, applications and technology architecture documentation and design artifacts
  • Help maintain the code and capability environment required to evolve data-driven, analytical capabilities with the end goal of understanding customer behavior and competitive dynamics
  • Strong experience with writing complex programs, implementing architectures, and enabling automation in these environments
  • The role will be responsible for providing innovative operational solutions and best practices
  • Communicate with various business areas, partner on the formulation of technical requirements for data ingestion, verification, scheduling, etc.
  • Strong written and verbal communication skills.

The Experience You Bring:

  • 5-7 years of experience in data modeling, data warehousing, and big data architectures
  • 5-7 years of experience of Amazon cloud (AWS)– S3, RDS, Lambda, Glue, SNS etc.
  • 5-7 years of experience in building data pipelines in tools using Apache Airflow
  • Good understanding of ETL/ELT experience and good knowledge of SQL and query optimization techniques
  • 3-5 years of experience with Snowflake.
  • Strong experience with databases such as Snowflake Postgres, Aurora, Athena
  • Strong programming experience with Python
  • Experience using GitHub, Bit Bucket, or other code repository solution
  • Understanding and knowledge of Automated code Deployments CI/CD

Business Acumen

  • Familiarity with Agile Methodologies.
  • Financial/ Investment Management industry experience

Problem Solving

  • Comfortable working with ambiguity (e.g. imperfect data, loosely defined concepts, ideas, or goals) and translating these into more tangible outputs

Leadership

  • Typically, no supervisory responsibilities but may provide informal guidance to new Team members
  • Leads projects and processed

Education Required

  • BS in Computer Science, Applied Mathematics, Physics, Statistics or area of study related to data sciences and data mining or relevant experience

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.

Average salary estimate

$100000 / YEARLY (est.)
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max
$80000K
$120000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Data Engineer, Invesco

Join Invesco in Atlanta, Georgia as a Data Engineer and be part of a dynamic team that’s reshaping the financial investment landscape! Invesco, a leader in asset management, is all about equipping investors with the tools they need to succeed. As a Data Engineer, you’ll engage with various teams to develop and manage large-scale data pipelines in a cloud environment, particularly using AWS technologies. Your role will involve supporting advanced analytics initiatives and ensuring seamless data integration. You'll collaborate closely with business and product owners to design innovative solutions that help our partners respond to an ever-evolving business environment. This position requires a strong technical skill set with experience in data modeling, data warehousing, and big data architectures. If you're someone who thrives on creating robust data solutions and enjoys working in a collaborative atmosphere, this is your chance to make a difference. Your expertise in tools like Apache Airflow and Snowflake, along with your proficiency in programming languages like Python, will be key to driving our projects forward. At Invesco, we believe in having a good work-life balance, which is why our flexible working model allows you to balance your time between our office and home. If you’re ready to dive into exciting challenges with smart colleagues while contributing to a company that values social responsibility, we want to hear from you!

Frequently Asked Questions (FAQs) for Data Engineer Role at Invesco
What qualifications do I need for the Data Engineer position at Invesco?

To qualify for the Data Engineer role at Invesco, you should have a BS in Computer Science, Applied Mathematics, Physics, Statistics, or a related field. Ideally, candidates should possess 5-7 years of experience in data modeling, data warehousing, and cloud technologies, predominantly AWS. Proficiency in building data pipelines using Apache Airflow and familiarity with ETL processes are also essential. Strong programming skills in Python and experience working with databases like Snowflake and Postgres will give candidates an advantage.

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What will my responsibilities be as a Data Engineer at Invesco?

As a Data Engineer at Invesco, you'll be responsible for managing and optimizing data integration platforms using AWS components, building data pipelines, and enabling accessibility for business reporting and analytics. You will also collaborate with various stakeholders to gather technical requirements and ensure that all projects align with Agile standards. Your role will include creating data architecture documentation and ensuring the availability of data for analytics initiatives.

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What technical skills are required for the Data Engineer role at Invesco?

For the Data Engineer position at Invesco, candidates should have a strong understanding of AWS services such as S3, RDS, Lambda, and Glue, alongside experience with data pipeline tools like Apache Airflow. Proficiency in SQL, query optimization techniques, and programming experience in Python are also necessary. A comprehensive understanding of big data architectures and a familiarity with Agile methodologies is beneficial for success in this role.

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How does Invesco support work-life balance for Data Engineers?

Invesco values work-life balance and offers a hybrid working model for its Data Engineers. As a full-time employee, you will work with your manager to create a flexible schedule that allows for at least three days in the office and two days remotely. This approach promotes a balance between collaborating with your team in person and enjoying the flexibility to work from home.

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What career development opportunities does Invesco provide to Data Engineers?

Invesco is committed to the professional growth of its employees. As a Data Engineer, you will have access to ongoing training programs and resources to enhance your skills in data engineering and analytics. The collaborative environment encourages sharing knowledge and best practices, enabling you to stay at the forefront of industry trends while fostering career advancement opportunities within the firm.

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Common Interview Questions for Data Engineer
Can you explain your experience with AWS and how it applies to the Data Engineer role at Invesco?

When answering this question, focus on specific AWS services you've utilized, such as S3, Lambda, or Glue, and demonstrate how you've implemented these tools in data engineering projects. Provide examples of challenges faced and how your solutions utilized AWS to improve data pipelines or analytics.

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Describe a time when you built a data pipeline using Apache Airflow. What challenges did you encounter?

Use the STAR method (Situation, Task, Action, Result) to structure your response. Detail the objective of the data pipeline you built, the technical challenges, such as scheduling or dependency management you faced with Airflow, and the outcomes of your efforts, particularly how you improved data processing efficiency.

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How do you ensure data quality and integrity when managing data pipelines?

Discuss specific strategies you've employed to ensure data quality, such as implementing validation checks, monitoring systems to detect anomalies, and creating clear documentation. Emphasize the importance of data integrity in supporting analytics initiatives and business decision-making.

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What methods do you use for optimizing SQL queries?

Provide insight into various optimization techniques, such as indexing, using EXPLAIN plans, and analyzing query performance. Discuss specific scenarios where you've successfully improved performance and the impact this had on overall data processing.

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How do you approach collaborating with cross-functional teams at Invesco?

Emphasize the importance of communication and collaboration in your work. Provide an example of a project where you successfully worked with different teams like business analysts or product owners to meet project goals, highlighting your ability to translate technical requirements into actionable insights.

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Can you share your experience with CI/CD processes in data engineering?

Discuss your familiarity with Continuous Integration and Continuous Deployment practices. Explain how you have implemented CI/CD solutions in past projects to automate deployments, streamline integration, and ensure high-quality code delivery in your data engineering workflows.

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In your opinion, what are the key challenges facing data engineers today?

Talk about current trends and challenges in the field, like data privacy concerns, the importance of real-time data processing, or the complexities of handling large datasets. Illustrate how staying informed and adaptable helps you overcome these obstacles.

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Describe a project where you utilized Snowflake as part of your data architecture.

Detail a specific project where you leveraged Snowflake, focusing on its capabilities and how it enhanced your solution's efficiency. Discuss how you managed data ingestion and query performance and the overall impact on business intelligence outcomes.

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What is your process for troubleshooting and debugging in a data pipeline?

Share your systematic approach to troubleshooting data pipelines, including identifying points of failure, using logs for analysis, and implementing solutions. Highlight how you ensure minimal disruption to analytics and reporting processes while resolving issues.

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How do you keep up with emerging technologies in data engineering?

Explain your proactive approach to learning about new technologies, such as attending workshops, participating in online courses, and following industry blogs. Share instances where you've recently adopted new tools or methodologies and how they have positively impacted your work.

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Helping investors worldwide achieve their financial objectives.

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DATE POSTED
April 8, 2025

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