FreshRemote.Work

Principal Data Engineer

Remote

Exactera has offices in New York City, Tarrytown NY, St. Petersburg FL, London, and Argentina. 

Compensation: $200,000- $240,000 depending on experience

We are a remote-friendly company, with offices in New York City, Tarrytown NY, St. Petersburg FL, London, and Argentina. For this role, we are happy to consider US-based candidates in the following states: AZ, CO, CT, DC, FL, GA, HI, IL, IN, LA, MA, MD, MI, MN, NC, NJ, NY, OH, PA, RI, SC, TN, TX, UT, VA, WA and WI, with preference to Eastern time zone residency.

Role Overview:
 
We are seeking an experienced data technologist for the role of Principal Data Engineer with a strong background in building reliable and distributed data systems across the public cloud.

In this role, you'll be instrumental in overseeing and developing data platforms for Exactera and an opportunity to build next-generation ETL pipelines across a diverse range of domains, including relational databases, data pipelines, multi-region data availability, data lakes, BI, and data-driven machine learning opportunities. 

Joining our fast-paced, dynamic team of experts, you will contribute to the development of scalable enterprise platforms in AWS. As a Principal Data Engineer, you will champion best practices and a well-architected approach to implementing cloud data solutions, covering industry-leading open source and cloud services such as observability, dataOps, data application deployments, Spark, Python, and other application and platform management technologies. Collaborating closely with our Engineering and Product teams, you will engineer, implement, and configure the full stack for data applications, while also influencing the architectural direction of cloud and data platform capabilities in alignment with the organization's goals and standards. This role demands experience in public cloud technologies and an exceptional enthusiasm for data engineering, demonstrated through a proven track record of self-motivated accomplishments.

Qualifications:

  • 8-12+ years working in data engineering, including big data, ETL, Spark/PySpark, data warehousing, and analytics application development. Demonstrated familiarity with underlying technology architectures rather than vendor solutions.
  • 8+ years of experience with query languages and database technologies.
  • 5+ years of experience working with cloud computing platforms such as AWS.
  • 5+ years of experience with Python and the Python ecosystem (PySpark, Pandas, DataFrames, etc.), showcasing the ability to write clean, maintainable, and robust code.
  • Experience ingesting files (XML/CSV) and normalizing data
  • Experience in building data pipelines in production and the ability to work across structured, semi-structured, and unstructured data.
  • Demonstrated experience working with external data vendors and managing data partnerships.
  • Experience with version control systems, preferably Git.
  • Ability to work in a Linux environment.
  • Strong knowledge of data & software engineering concepts and best practices.
  • Experience in preparing data for analytics and following data workflows.
  • Knowledge of systems monitoring tools in a cloud environment.

 

 

Nice To Haves:

  • The ideal candidate can demonstrate the ability to deliver value to clients that drive positive business outcomes.
  • Has been a tech lead or technical leader on an empowered engineering team, working closely with a product manager and clients to understand the feasibility of building minimum viable features.
  • Experience working with Terraform for Infrastructure as Code (IaC) in AWS.
  • Experience working with LLMs/ML/AI.
  • Fintech background is a bonus. 

What You Need to Succeed:

  • Designing and deploying medium to big data applications fit for purpose across scaling, throughput, and high-availability dimensions.
  • A focus on DORA/DevOps delivery best practices including delivering to production frequently with small batch sizes, focusing on learning from clients.
  • Working with global teams and product owners, providing industry-leading cloud data solutions and applying best practices.
  • Supporting security policies, standards, and processes based on current and previous business requirements. 
  • Creating and maintaining comprehensive documentation.
  • Partnering with operations teams to onboard business-as-usual work and automation to the appropriate groups.
  • Creating and deploying robust and reusable config management solutions.

What We Offer:

Great team culture, career development, great compensation package and benefits, and an unparalleled experience as part of one of the most advanced teams in the world. With a company culture that provides ample opportunities to be recognized, build valuable skills, and grow your career.

About Us:

Exactera, a pre-IPO SaaS company, is the global leader in technology driven tax solutions. Founded in 2016, we stand at the intersection of human and machine intelligence. We have offices in New York, Florida, London and remote employees across the United States and Argentina.  Through our AI and cloud-based technologies, we deliver superior solutions to our corporate tax customers. As a result, Savant Venture Fund and Insight Partners have invested over $100 million in funding to support our growth.

We are committed to promoting the values of diversity and inclusion throughout the business. Whether it is through recruitment, retention, career progression or training and development, we are committed to improving opportunities for our people regardless of their background or circumstances.

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Job Profile

Restrictions

Preference for eastern time zone residency US-based candidates only

Benefits/Perks

Benefits Career development Compensation package Compensation package and benefits Dynamic team Great compensation package Great compensation package and benefits Great team culture Opportunity for growth Remote Friendly Team culture

Tasks
  • Build ETL pipelines
  • Collaborate with teams
  • Engineer data applications
  • Influence architectural direction
  • Oversee data platforms
Skills

AI Analytics AWS Big Data Data application deployments Data-driven machine learning Data engineering Data Lakes DataOps Data Pipelines Data Warehousing Data Workflows ETL Git Infrastructure as Code Linux ML Observability PySpark Python Spark

Experience

8-12 years

Education

Engineering

Timezones

UTC-5