Data Engineer

Artlogic
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior

Job location

Remote

Tech stack

Clean Code Principles
Microsoft Excel
API
Artificial Intelligence
Unit Testing
C Sharp (Programming Language)
Cloud Computing
Software Quality
Data Validation
Data Integrity
ETL
Data Mapping
Data Transformation
Data Migration
Data Structures
Relational Databases
Database Storage Structures
FileMaker
Systems Analysis
JSON
Python
NoSQL
Object-Oriented Software Development
Regular Expressions
Ruby
SQL Databases
Technical Data Management Systems
XML
Pandas
REST

Job description

As a Junior Data Engineer , you will be a vital part of the team responsible for the lifeblood of our onboarding process: client data. You will help bridge the gap between legacy client systems and the Artlogic ecosystem by building and executing robust ETL (Extract, Transform, Load) pipelines.

This role is ideal for a developer early in their career who loves the "puzzle" aspect of data. You will work within the Data Migration team to dismantle complex external data structures (Relational data, FileMaker), reassemble them into our sophisticated data model, and contribute to the internal Python/Ruby libraries that make our migrations faster and smarter. You will be mentored by senior engineers and work closely with Project Managers to ensure a seamless transition for our clients. Key Responsibilities ETL Development & Execution

  • Execute End-to-End Migrations: Learn to navigate the full migration lifecycle, moving data from diverse client environments into Artlogic.
  • Extraction: Use scripts and tools to pull data from external platforms (e.g., FileMaker, legacy SQL databases).
  • Transformation: Write clean, maintainable code to map, clean, and transform "messy" legacy data to fit the Artlogic schema.
  • QA & Validation: Perform rigorous data validation and unit testing to ensure 100% accuracy and data integrity before go-live.

Technical Growth & Tooling

  • Code Contribution: Assist in developing and maintaining our internal migration frameworks and R&D tools.
  • Pipeline Optimization: Identify repetitive tasks in your daily workflow and work with senior engineers to automate them.
  • Systems Analysis: Research unknown database structures to determine the most efficient extraction methods.

Collaboration & Project Delivery

  • Cross-functional Teamwork: Partner with Client Liaison Project Managers to understand client-specific data nuances.
  • Documentation: Document migration mappings and technical edge cases to ensure knowledge is shared across the team.
  • Iterative Delivery: Adapt migration scripts quickly as project requirements evolve during the onboarding phase.

AI & Data

  • AI Recommendation Verification and Data Mapping: Review and verify AI (Claude) recommendations for column mappings during cloud data migration, including confirming that columns fit perfectly or identifying where data requires manipulation or concatenation.
  • Data Transformation and Cloud Push: Perform final data transformation steps using basic Python, Pandas, and Reax code to prepare and push relational data from Excel into the cloud environment.

Key Attributes

  • Data Integrity: Success is measured by the accuracy of migrated data and the absence of "broken" records post-launch.
  • Technical Progression: Demonstrates a growing ability to handle increasingly complex data structures with less supervision.
  • Code Quality: Contributions to internal libraries follow team standards and improve overall migration speed.
  • Reliability: Consistently meets project milestones and keeps stakeholders informed of technical blockers.

Requirements

  • Coding Foundations: Proficiency in at least one object-oriented language- Python is preferred, but we also value strong logic in C#.
  • SQL & Data Logic: Solid understanding of relational databases (Joins, Keys, Indexes) and how to manipulate data structures.
  • Problem-Solving Mindset: You enjoy the "detective work" of figuring out how a legacy system was built and how to extract its value.
  • Detail Oriented: An obsession with data accuracy; you catch the "edge case" before it becomes a bug.
  • Communication: Ability to explain technical data hurdles to non-technical Project Managers.

Desirable

  • The "Data Stack": Experience with ETL tools, pandas (Python), or regular expressions (Regex).
  • API Knowledge: Familiarity with REST APIs and how to handle JSON/XML data.
  • Niche Systems: Previous exposure to FileMaker (Claris) or NoSQL environments.
  • Web Basics: A high-level understanding of how back-end data interacts with front-end UIs.

About the company

Artlogic is a leading technology platform for the art world. Founded in 1989, Artlogic empowers over 6,000 galleries, dealers, and art professionals worldwide to streamline their operations and grow their businesses. The company's integrated platform combines inventory management, CRM, websites, sales, marketing, and payment tools, everything needed to run a modern and successful art business. In 2021, Artlogic was acquired by tech investors Cove Hill Partners to accelerate innovation and expand its global reach. Since then, the company has doubled in size, with employees across London, New York, Atlanta, and Cape Town. Today, Artlogic is entering an exciting new chapter through its merger with ArtCloud, another industry leader in art technology. Together, the two companies are uniting complementary platforms to build the most comprehensive, forward-thinking solution for the art world. This collaboration brings together deep expertise across CRM, sales, marketing, inventory, payments, and AI-powered tools, empowering galleries, artists, and collectors worldwide. Joining Artlogic means becoming part of a growing global team that is shaping the future of how art is bought, sold, and managed, both online and in person. The Data Migration team operates within the Customer function, combining both technical and project delivery responsibilities. Project Managers act as the primary client interface, coordinating communication and requirements. Data Migration Specialists are responsible for technical execution, including ETL processes and solution design The team also contributes to internal R&D, building tools and applications to improve migration efficiency and scalability

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