FreshRemote.Work

Customer Integration Engineer (Data Engineer)

Poland

Role: Customer Integration Engineer (Data Engineer)
Location:
Fully remote in Poland
Type: This can be structured as a B2B contract at $120k - 140k USD annually + stock options or as an Employment Contract with full benefits at $100k - 120k USD + stock options

Who we are

Focal Systems is the industry leader in retail AI solutions. We are a Silicon Valley based startup that has more than doubled in size every year since inception. We are a Deep Learning first company. Our mission is to automate and optimize brick and mortar retail using deep learning computer vision. Focal Systems has been deployed at scale with the top retailers in the world. We are looking for smart, creative and passionate people who want to help build a great and enduring company and deploy Deep Learning to the world!

We have a strong team of engineers located in Poland.


What we are looking for

We are seeking a skilled Customer Integration Engineer specializing in customer data transformation to play a crucial role in transforming diverse customer data into standardized, high-quality datasets that power our business operations. In this role, you will focus on analyzing, cleaning, and transforming customer data to meet our specific data needs and ensure seamless integration into our systems.

What you will do

  • Partner with the sales team to smoothly integrate new customers into our system and manage optimal roll-out timelines
  • Design and implement data transformation processes to convert customer data into our required formats and schemas
  • Analyze complex customer data structures and formats to determine optimal transformation strategies
  • Develop and maintain ETL pipelines for efficient customer data ingestion and transformation
  • Perform thorough data quality assessments and implement data cleaning procedures to ensure accuracy and consistency of transformed data
  • Optimize data transformation queries and processes for improved performance across multiple database technologies
  • Collaborate with cross-functional teams to understand customer data requirements and deliver effective transformation solutions
  • Create and maintain documentation for data transformation processes and mappings
  • Implement data validation checks to ensure transformed data meets our specification

What you need to be successful

  • Bachelor's or Master's degree in Computer Science, Data Engineering or related field
  • 5+ years of experience in data engineering with a focus on data transformation and integration
  • Proficiency in at least three of the following database technologies:
    • MySQL
    • Redis
    • Google BigQuery
    • MongoDB
  • Strong skills in data profiling, cleansing, and transformation techniques
  • Proficiency in Python and SQL for complex data manipulation and transformation
  • Experience with ETL tools and frameworks for large-scale data processing
  • Demonstrated ability to handle diverse data formats (e.g., CSV, JSON, XML, APIs)
  • Advanced knowledge of SQL for complex data transformations and query optimization
  • Expertise in data modeling and schema design for efficient data storage and retrieval
  • Strong analytical and problem-solving skills, particularly in resolving data inconsistencies
  • Experience with data mapping and reconciliation between different data models
  • Proficiency in writing efficient and scalable data transformation scripts
  • Excellent attention to detail and commitment to data accuracy

Preferred Skills: 

  • Experience with real-time data processing and streaming technologies for continuous data transformation
  • Familiarity with data governance principles and data privacy regulations
  • Knowledge of industry-specific data standards and formats
  • Experience with version control systems (e.g., Git) for managing transformation code

What we offer

We care deeply about the health, happiness, and wellbeing of all of our employees. We offer:

  • Competitive Salary & Attractive Stock
  • Paid Time Off 
  • Quarterly Team Retreats
  • Opportunity to work on challenging customer data transformation projects
  • Access to modern data processing tools and technologies
  • Professional development opportunities and conference attendance
  • Collaborative work environment focused on data quality and efficiency

 

Note: Our pay bands are driven by market benchmarks in the target geography for hiring. Our posted ranges typically include multiple job levels. A candidate's level is determined by their performance throughout our talent acquisition process including technical screens, behavior interviews, presentations, work samples, and references. We will communicate transparently with the candidate at final stages regarding how we have leveled them, and what salary range that places them into. Placement within range is equally determined by education, general experience in your profession, specific experience in our domain, and your performance in the talent acquisition process. It is rare to receive an offer at the top of the range for a role.

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Job Profile

Regions

Europe

Countries

Poland

Restrictions

Fully remote Fully remote in Poland

Benefits/Perks

Competitive salary Full benefits Fully remote Health and wellness support Paid Time Off Professional development Quarterly team retreats Stock options

Tasks
  • Analyze customer data structures
  • Collaborate with teams
  • Create documentation
  • Design data transformation processes
  • Develop ETL pipelines
  • Implement data validation checks
  • Integrate new customers
  • Optimize transformation queries
  • Perform data quality assessments
Skills

Computer Vision Data cleansing Data Governance Data Integration Data Mapping Data Modeling Data privacy Data Profiling Data reconciliation Data Transformation Deep Learning ETL Git Google BigQuery MongoDB MySQL Python Real-time data processing Redis Sales Schema design SQL Streaming technologies

Experience

5 years

Education

Bachelor's degree Computer Science Data Engineering Engineering Master's degree Related Field

Timezones

Europe/Warsaw UTC+1