Jobs Data Engineer

Start date: ASAP

What you’ll do

• Build and maintain scalable data ingestion pipelines into Snowflake (structured + time-series data)
• Transform raw data into ML-ready datasets (feature engineering, windowed aggregations, lag variables, train/test splits)
• Develop and operationalize ML models in Python (scikit-learn, XGBoost, LightGBM)
• Work within Snowflake using Snowpark to productionize models
• Write model outputs back into Snowflake for AI-driven applications and downstream services
• Ensure production reliability of pipelines and models (monitoring, retraining triggers, data quality checks)

What we’re looking for

• Strong Python skills (data engineering + ML)
• Solid Snowflake experience (SQL, Streams, Tasks, Snowpipe, ingestion patterns, basic performance tuning)
• Hands-on ML experience — you can build, train and deploy models yourself
• Understanding of ML lifecycle in production environments
• Experience with time-series data (window features, irregular series, forecasting) — nice to have
• Familiarity with Azure Data Lake / Azure Fabric — nice to have

Why this role is interesting

• Real AI product impact — not just pipelines, but production ML
• Ownership of end-to-end ML workflows
• Modern stack: Snowflake + Snowpark + Python ML ecosystem
• High autonomy and engineering-driven culture
• Long-term stable project

We are looking for a Senior Data Engineer. This is not a standard ETL role. You will work on a high-load system processing 10,000+ executions per minute, building scalable pipelines where AI and LLM logic are embedded directly into production data flows.

The role combines data engineering, backend thinking, infrastructure ownership, and real production AI integration.

What you will do:

• Design and maintain scalable data pipelines in Python on Google Cloud Platform
• Build and optimize AI-driven scoring flows using LLMs for real-time identity enrichment
• Work with BigQuery, Apache Spark, and Apache Iceberg for heavy data processing
• Maintain high-load orchestration with custom Python nodes and complex workflows
• Own deployment and release processes (CI/CD)
• Optimize PostgreSQL performance under heavy load
• Investigate incidents and resolve root causes permanently

• Use AI engineering tools such as Claude in daily development

   

Requirements:

• 4+ years of experience in Data Engineering / Backend Engineering
• Strong Python skills
• Commercial experience with production LLM integration (OpenAI / Anthropic / Gemini)
• Strong knowledge of GCP (Cloud Functions, IAM, Networking)
• Experience with BigQuery, Spark, Iceberg
• Good understanding of Kubernetes
• Experience with workflow orchestration tools (n8n is a strong plus)
• Strong practical knowledge of PostgreSQL

• English level B2+

   

What is important for us:

• Ownership mindset
• Fast learning ability
• Strong problem-solving approach
• Active AI usage in engineering work
• Focus on practical results over unnecessary complexity

Join a Company That Invests in You

Seeking Alpha is the world’s leading community of engaged investors. We’re the go-to destination for investors looking for actionable stock market opinions, real-time market analysis, and unique financial insights. At the same time, we’re also dedicated to creating a workplace where our team thrives. We’re passionate about fostering a flexible, balanced environment with remote work options and an array of perks that make a real difference.

Here, your growth matters. We prioritize your development through ongoing learning and career advancement opportunities, helping you reach new milestones. Join Seeking Alpha to be part of a company that values your unique journey, supports your success, and champions both your personal well-being and professional goals.

What We're Looking For

Seeking Alpha is looking for a Senior Data Engineer responsible for designing, building, and maintaining the infrastructure necessary for analyzing large data sets. This individual should be an expert in data management, ETL (extract, transform, load) processes, and data warehousing and should have experience working with various big data technologies, such as Hadoop, Spark, and NoSQL databases. In addition to technical skills, a Senior Data Engineer should have strong communication and collaboration abilities, as they will be working closely with other members of the data and analytics team, as well as other stakeholders, to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with the overall business goals and objectives.

The Senior Data Engineer will be engaged with the company as a contractor (Private Entrepreneur).

What You'll Do

• Work closely with data scientists/analytics and other stakeholders to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with business goals and objectives
• Design, build and maintain optimal data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources, including external APIs, data streams, and data stores. 
• Continuously monitor and optimize the performance and reliability of the data infrastructure, and identify and implement solutions to improve scalability, efficiency, and security
• Stay up-to-date with the latest trends and developments in the field of data engineering, and leverage this knowledge to identify opportunities for improvement and innovation within the organization
• Solve challenging problems in a fast-paced and evolving environment while maintaining uncompromising quality.
• Implement data privacy and security requirements to ensure solutions comply with security standards and frameworks.
• Enhance the team's dev-ops capabilities.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 2+ years of proven experience developing large-scale software using an object-oriented or functional language.
• 5+ years of professional experience in data engineering, focusing on building and maintaining data pipelines and data warehouses
• Strong experience with Spark, Scala, and Python, including the ability to write high-performance, maintainable code
• Experience with AWS services, including EC2, S3, Athena, Kinesis/Firehose Lambda and EMR
• Familiarity with data warehousing concepts and technologies, such as columnar storage, data lakes, and SQL
• Experience with data pipeline orchestration and scheduling using tools such as Airflow
• Strong problem-solving skills and the ability to work independently as well as part of a team
• High-level English - a must. 
• A team player with excellent collaboration skills.

Nice to Have:

• Expertise with Vertica or Redshift, including experience with query optimization and performance tuning
• Experience with machine learning and/or data science projects
• Knowledge of data governance and security best practices, including data privacy regulations such as GDPR and CCPA.
• Knowledge of Spark internals (tuning, query optimization)

Our client is seeking a motivated and skilled Data Engineer to join their core Data Engineering team. This is a hands-on role designed for a technical expert who enjoys building robust data architectures and working directly with the Modern Data Stack

As a Data Engineer, you will be responsible for designing, developing, and optimizing data transformation pipelines. You will play a crucial role in turning raw data into actionable insights by leveraging Snowflake and dbt to ensure high-quality, scalable data delivery.
 

Key Responsibilities:

• Design and build sophisticated SQL models to process both batch and near real-time data streams.
• Utilize dbt to implement reliable, version-controlled transformation logic.
• Ensure high performance and cost-efficiency within the Snowflake environment.
• Build and maintain scalable ELT/ETL processes to support the organization's evolving data needs.

Skills & Experience:

• Proven experience working with Snowflake architecture (Virtual Warehouses, Snowpipe, etc.).
• Strong proficiency in using dbt for modular data modeling and testing.
• Expert-level ability to write complex, performant, and clean SQL code.
• Solid understanding of data warehousing concepts, schema design (Star, Snowflake, Data Vault), and data lifecycle management.
• A proactive approach to problem-solving and a passion for deep-diving into technical challenges.

Nice to Have:

• Real-time Processing: Previous experience building SQL models specifically for real-time data pipelines.
• Experience with orchestration tools (e.g., Airflow, Dagster) or cloud platforms (AWS/Azure/GCP).

Project Overview

UADAMAGE is hiring a Data Engineer to join a cross-functional team working on a national-scale Big Data platform for Ukraine. The project focuses on building a geospatial platform for multifactor analysis of territories to support demining and recovery planning. The system integrates remote sensing, environmental and socio-economic indicators, and includes both Big Data infrastructure and AI/ML modules. The platform is under active development with support from governance and international partners.

Role Summary

Design and maintain scalable and sustainable data pipelines within the platform to ensure timely, accurate, and consistent integration of multi-source data. Develop and support workflows for data ingestion, cleansing, normalization, and transformation from internal and external sources (e.g. government systems, commercial registers, API feeds). Ensure compatibility of all data pipelines with downstream use in GIS systems, land analysis models, dashboards and reports. Execute basic data analysis. Collaborate with product, analytics, and engineering teams to maintain data quality and feasibility for decision-support tools. Support data architecture evolution, implement data processing best practices, and contribute to technical documentation.

Qualifications required

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related fields.
• 3+ years of experience in data engineering or data platform development.
• Proven experience in building and maintaining data pipelines (ETL/ELT), performing data cleansing, normalization, and transformation of structured and unstructured datasets.
• Hands-on experience with technologies such as Python, PySpark, Scala, SQL, Pandas, NumPy and tools including Apache Spark, Hadoop, and Amazon EMR.
• Experience working with AWS-based platforms, including S3 and cloud-native data processing services.
• Practical knowledge of streaming frameworks and distributed data processing patterns, such as MapReduce and real-time cloud pipelines.
• Experience integrating data from diverse sources (relational databases, APIs, satellite/geospatial data, file systems) for use in analytical models and data management platforms.
• Understanding of data integration strategies, API/data services, and long-term system maintainability.
• Familiarity with best practices in data documentation, versioning, metadata tracking, and validation.
• Familiarity with geospatial data formats, geo coordinate systems, and spatial preprocessing is an asset.
• Experience working in complex or multi-stakeholder environments is an asset.

• Proficiency in Ukrainian and English is required.

   

We offer

• Competitive salary
• Motivated and engaged team
• Open communication and active knowledge sharing
• Direct support from project leadership
• Clear specifications and well-defined requirements
• Opportunity to contribute to a high-impact, nationally relevant initiative

Location: Europe (remote, occasional workshops)
Start: ASAP | Duration: until 15.12.2026

Role Overview

We are looking for an Azure Databricks Data Engineer to build and scale data foundations for an AI-driven platform in the energy sector.

This role is focused on delivering high-quality, governed, AI-ready data products that power autonomous agents, semantic data access (Genie), and advanced analytics.

What You’ll Do

• Build scalable data products on Azure & Databricks (Delta Lake, Unity Catalog)
• Develop robust data pipelines (ingestion, transformation, harmonization)
• Prepare and structure data for AI agents and Genie-based access
• Enable discoverable, interpretable, and reusable datasets
• Collaborate closely with AI/Agent & Backend Engineers in a shared backlog
• Ensure data governance, quality, and security standards
• Contribute to data standards and AI data best practices

Your Profile

• Strong hands-on experience with Azure & Databricks
• Solid background in data engineering & data modeling
• Proven experience building data pipelines & data products
• Strong SQL & Python skills
• Experience with Delta Lake & Unity Catalog
• Understanding of AI/ML data preparation

Nice to Have

• Experience with Genie or semantic data layers
• Exposure to agent-based or AI-driven systems
• Background in energy / renewables

Working Style

• Cross-functional, product-oriented team
• High autonomy, fast iterations
• Shared ownership of end-to-end delivery
• Strong focus on AI enablement through data
•  

Google Cloud Solutions Architect / Pre-Sales Engineer

Company: Softprom Solutions
Location: Remote (Ukraine)
Employment: Full-time, FOP (contractor)

About the role

Softprom Solutions is looking for a Google Cloud Solutions Architect / Pre-Sales Engineer to join our Cloud team.

This role is ideal for a specialist with hands-on experience in Google Cloud Platform and an active Google Cloud certification, who wants to work on real commercial projects, participate in pre-sales activities, and grow in cloud architecture.

Responsibilities

• Design and document Google Cloud architectures according to the Google Cloud Architecture Framework
• Participate in pre-sales activities:
  • technical discovery with customers
  • solution design
  • participation in demos and presentations
• Deployment and configuration of core GCP services, including:
  • Compute Engine, Cloud Storage, Cloud SQL
  • VPC, IAM, Load Balancing
  • Cloud Functions / Cloud Run
• Design and configure GCP networking:
  • VPC networks, subnets
  • Firewall rules
  • Routes
• Implement and support Infrastructure as Code (IaC) using Terraform
• Create technical and solution documentation
• Act as a technical point of contact for sales and customers

Requirements (Must have)

• Active Google Cloud certification
  (Associate Cloud Engineer or Professional Cloud Architect)
• Experience as Cloud Engineer / Solutions Architect / Pre-Sales Engineer
• Practical understanding of Google Cloud core services:
  • Compute, Storage, Databases, Networking, Security
• Solid networking knowledge:
  • TCP/IP (L3, L4)
  • IP addressing, subnetting
  • DNS
• Understanding of cloud principles:
  • High Availability
  • Fault Tolerance
  • Scalability
  • Security
• Linux skills (command line)

Nice to have

• Experience in pre-sales or customer-facing roles
• Experience with Terraform
• Basic scripting skills (Python, Bash)
• Experience with Docker, Kubernetes (GKE), Cloud Run
• Experience with AWS or multi-cloud environments

Soft skills

• Ability to communicate technical solutions to non-technical audiences
• Structured and analytical thinking
• Proactivity and ownership
• Ukrainian — fluent
• English — reading and basic spoken (technical / pre-sales)

We offer

• Compensation: $2000 USD + project-based bonuses
• FOP cooperation
• Full-time workload
• Real commercial Google Cloud projects
• Participation in pre-sales and architecture design
• Professional growth in Cloud & Solutions Architecture
• International projects and vendors
• Strong cloud team and mentorship

AWS Cloud Engineer

Softprom Solutions
Azerbaijan | Remote / Hybrid
Full-time | Contractor (Individual Entrepreneur)
Contract with Austria

About Softprom

Softprom Solutions is an international IT distributor and solutions provider working with leading global vendors in Cloud, Cybersecurity, Infrastructure, and Enterprise IT.

We are expanding our Cloud Practice and are looking for an AWS Cloud Engineer in Azerbaijan who wants to grow professionally, work on real customer projects, and collaborate with international teams under an Austrian contract.

About the role

This role is ideal for an AWS-certified engineer with solid fundamentals who wants to deepen hands-on experience in cloud architecture, deployments, automation, and customer-facing work.

You will work closely with senior architects, sales teams, and customers, participating in both technical delivery and pre-sales activities.

Responsibilities

• Support the design and documentation of AWS cloud architectures following the AWS Well-Architected Framework
   
• Participate in deployment and configuration of core AWS services, including
  VPC, EC2, S3, RDS, IAM, Lambda, Load Balancers
   
• Assist with AWS networking configuration:
  Subnets, Route Tables, Security Groups, NACLs
   
• Contribute to automation and Infrastructure as Code (IaC) initiatives using
  Terraform and/or AWS CloudFormation
   
• Create and maintain technical documentation for architectures and configurations
   
• Participate in customer meetings, presentations, and demos, explaining AWS solutions and capabilities
  
   

Requirements (Must have)

• Active AWS Certified Solutions Architect – Associate (SAA-C03)
   
• Solid theoretical understanding of AWS core services:
  Compute, Storage, Databases, Networking, Security
   
• Basic networking knowledge:
  TCP/IP (L3, L4), IP addressing, subnetting, DNS
   
• Understanding of cloud principles:
  High Availability, Fault Tolerance, Scalability, Security
   
• Basic Linux skills (command line)
   
• Ability to read and understand technical documentation in English
  
   

Nice to have

• Hands-on experience with Terraform or CloudFormation
   
• Basic scripting skills (Python, Bash)
   
• Familiarity with Docker, Kubernetes, ECS
   
• Personal, educational, or non-commercial projects deployed on AWS
  
   

Soft skills

• Strong motivation to learn and grow in cloud engineering
   
• Structured and analytical thinking
   
• Clear and confident communication
   
• Ukrainian or Russian — fluent
   
• English — reading technical documentation (spoken English is a plus)
  
   

We offer
 

• Individual Entrepreneur (FOP) / contractor model
   
• Official contract with Austria
   
• Full-time workload
   
• Real commercial AWS projects (not internal labs)
   
• Participation in architecture design and pre-sales activities
   
• Professional growth within Cloud & Solutions Architecture
   
• International customers and vendors
   
• Supportive, senior cloud team and mentorship

Description:

Our Client is the fast-paced digital healthcare company which creates the growing portfolio of online health communities for people with chronic conditions. Company’s mission is to improve patient’s quality of life by connecting them with each other, with caregivers and healthcare industry partners, building beneficial social interactions and meaningful health conversations. 
 

About the project:
The core of the project is working with the data; the target is to re-design and enhance data-driven solutions. The team is responsible for expanding and optimizing the data flow and data pipeline architecture, model and analyze data, interpret trends or patterns in complex data sets and translate them into product and marketing insights. If you are excited by the prospect of optimizing or even re-designing our data architecture to support our next generation of products and data initiatives, we would be thrilled to have you apply!

Requirements:

● Good Python skills

● Good working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases

● A successful history of manipulating, processing and extracting value from large disconnected datasets

● Experience building and optimizing data pipelines, architectures and data sets

● Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

● Strong analytic skills related to working with unstructured datasets

Technologies:

• Python
• AWS: SES, RDS (MySQL), EC2, Elasticsearch Service, Route 53, VPC, etc
• Snowflake
• Docker
• dbt
• Airflow
   

Job responsibilities:

● Manage and optimize core data infrastructure

● Develop custom data infrastructure not available off-the-shelf

● Build monitoring infrastructure to give visibility into the pipeline’s status

● Monitor all jobs for impact on cluster performance

● Run maintenance routines regularly

● Tune table schemas to minimize costs and maximize performance

● Build and maintaining custom ingestion pipelines

● Build non-SQL transformation pipelines

● Build processes supporting data transformation, data structures, metadata, dependency and workload management

We are looking for a Data Engineer to join our team!

Data Engineer is responsible for designing, maintaining, and optimizing data infrastructure for data collection, management, transformation, and access.

He/she will be in charge of creating pipelines that convert raw data into usable formats for data scientists and other data consumers to utilize.

Data Engineer should be comfortable working with RDBMS and has a good knowledge of the appropriate RDBMS programming language(s) as well.

The Data Engineer fulfills processing of client data based on proper specification and documentation.

     Main responsibilities:

• Design and develop ETL pipelines;
• Data integration and cleansing;
• Implement stored procedures and function for data transformations;
• ETL processes performance optimization.

     Skills and Requirements:

• Experience with ETL tools (to take charge of the ETL processes and performs tasks connected with data analytics, data science, business intelligence and system architecture skills);
• Database/DBA/Architect background (understanding of data storage requirements and design warehouse architecture, should have the basic expertise with SQL/NoSQL databases and data mapping, the awareness of Hadoop environment);
• Data analysis expertise (data modeling, mapping, and formatting, data analysis basic expertise is required);
• Knowledge of scripting languages (Python is preferable);
• Troubleshooting skills (data processing systems operate with large amounts of data and include multiple structural elements. Data Engineer is responsible for the proper functioning of the system, which requires strong analytical thinking and troubleshooting skills);
• Tableau experience is good to have;
• Software engineering background is good to have;
• Good organizational skills, and task management abilities;
• Effective self-motivator;
• Good communication skills in written and spoken English.

     Salary Range

Compensation packages are based on several factors including but not limited to: skill set, depth of experience, certifications, and specific work location.

About the client
Haptiq is an AI-native enterprise solutions company with purpose-built technology for public & private companies, governments, institutions, asset managers, and family offices

With headquarters in New York City and four global offices, Haptiq is supported by more than 300 engineers and delivery professionals across the globe. By centralizing and unifying data, automating workflows, and surfacing predictive insights, Haptiq enables organizations to scale operational excellence and generate alpha across complex enterprise environments

The Opportunity
This position is for a Cloud Data Engineer with a background in Python, DBT, SQL, and data warehousing for enterprise-level systems
 

Responsibilities and Duties
— Design, develop, and deploy Python scripts and ETL processes with Prefect and Airflow to prepare data for analysis
— Model dimensional and denormalized schemas for optimal performance reporting and discovery
— Design AI-friendly DB schemas and ontologies
— Architect cloud ops solutions for data topologies
— Transform and migrate data with Python, DBT, and Pandas
— Work with event-based/streaming technologies for real-time ETL
— Ingest and transform structured, semi-structured, and unstructured data
— Optimize ETL jobs for performance and scalability to handle big data workloads
— Monitor and troubleshoot ETL jobs to identify and resolve issues or bottlenecks
— Implement best practices for data management, security, and governance with Prefect, DBT, and Pandas
— Write SQL queries and program stored procedures and reverse engineer existing data pipelines
— Perform code reviews to ensure fit to requirements, optimal execution patterns, and adherence to established standards
— Assist with automated release management and CI/CD processes
— Validate and cleanse data and handle error conditions gracefully
 

Requirements
— 3+ years of Python development experience, including Pandas
— 5+ years writing complex SQL queries with RDBMSes
— 5+ years of Experience with developing and deploying ETL pipelines using Airflow, Prefect, or similar tools
— Experience with cloud-based data warehouses in environments such as RDS, Redshift, or Snowflake
— Experience with data warehouse design: OLTP, OLAP, Dimensions, and Facts
— Experience with cloud-based data architectures, messaging, and analytics
— Bachelor’s degree in Computer Science or equivalent — preferred
 

Pluses — Experience with
— Docker
— Kubernetes
— CI/CD automation
— AWS lambdas/step functions
— Data partitioning
— Databricks
— Pyspark
— Cloud certifications
 

Why Join Us?
We value creative problem solvers who learn fast, work well in an open and diverse environment, and enjoy pushing the bar for success ever higher. We do work hard, but we also choose to have fun while doing it

We are looking for a Data Engineer to join our partner team.

The primary goal of this role is to design, build, and maintain a scalable data infrastructure that supports analytics, reporting, and data-driven decision-making across the organisation.

This role focuses on developing reliable data pipelines, integrating multiple data sources, ensuring data quality, and delivering business-oriented data solutions aligned with company goals.

What you will do:

• Development and maintenance of ELT processes for collecting, transforming, and loading data from various sources into BigQuery.
• Creation and development of a dbt project to build data models (stage, base, intermediate, dimension, report layers) used in analytics and reporting.
• Optimization of performance of pipelines, SQL queries, and data models.
• Validation, testing, and data quality control at all stages of the pipeline.
• Setting up monitoring and alerting for data pipelines and key infrastructure components.
• Integration of data from various sources (mobile application, financial and marketing information), including APIs and external systems.
• Collaboration with analysts to ensure data is properly structured, easy to use, and supports the team’s analytical needs.
• Maintaining up-to-date documentation regarding data architecture, ELT processes, and dbt models.
• Tools you will work with: SQL, Python, dbt, and GCP cloud services for building and maintaining data pipelines.

What we expect from you:

• 3+ years of experience in a Data Engineer position or a related role with a strong focus on building pipelines and data modeling.
• Deep knowledge of SQL: complex queries, optimization, understanding of Data Warehousing principles.
• Practical experience working with BigQuery, Snowflake, Redshift, or other analytical warehouses.
• Experience working with dbt, including testing, documentation, and CI/CD integration.
• Experience building and maintaining ELT/ETL pipelines.
• Strong proficiency in Python for integrations, automation, and data processes.
• Confident use of Git and experience working with GitHub/GitLab.
• Experience working with GCP or other cloud platforms.
• Attention to detail, strong problem-solving mindset, and ownership of results.
• Experience collaborating with analysts and understanding their data needs.
• Nice to have:
• Experience optimizing cost efficiency and query performance in cloud environments.
• Experience working with real-time / streaming data solutions.
• Ability to clearly explain technical solutions to stakeholders.

Hi there! AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

Why join us
If you’re looking for a place to grow, make an impact, and work with people who care, we’d love to meet you! :)

About the role
As a Data Steward, you will play a key role in ensuring high-quality, reliable product data that directly impacts sales performance across the EMEA market. This role sits at the intersection of business and technology, shaping how product information flows through PIM systems and reaches external channels. You’ll have real influence on data standards, processes, and visibility, while collaborating with diverse stakeholders in a structured yet supportive environment. It’s an opportunity to grow your expertise in data stewardship, product information management, and cross-functional collaboration within a global setup.

What you will do
● Validate that mandatory product data provided by business teams is accurate and complete;
● Upload product data into the PIM system and resolve data gaps, including coordinating with multiple stakeholders to complete missing information;
● Syndicate product data into channel-specific templates and resolve any related issues;
● Support business teams when they encounter issues using product data for the channel;
● Clarify and communicate data issues and requirements to stakeholders to ensure data quality and accuracy;
● Create, track, and report on the status of product data requests;
● Reconfigure and maintain syndication templates in inRiver.

Must haves
● Minimum of 3 years of experience in data management, with solid knowledge of core principles and concepts;
● Good understanding of the data lifecycle;
● Ability to use multiple tools to create and maintain data stewardship processes, inputs, and outputs;
● Hands-on experience with Inriver is required; alternatively, experience with Salsify, Informatica, or Akeneo (in complex implementations) will be considered;
● Experience working with retailers and marketplaces, including PIM syndication setup and management;
● Strong Excel skills;
● Ability to work efficiently under tight and ongoing deadlines;
● Strong communication skills, with the ability to interact with both business and technical stakeholders;
● Fluent written and spoken English.

Perks and benefits
● Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
● Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
● A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
● Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office — whatever makes you the happiest and most productive.


Meet Our Recruitment Process
Asynchronous stage — An automated, self-paced track that helps us move faster and give you quicker feedback:
● Short online form to confirm basic requirements
● 30–60 minute skills assessment
● 5-minute introduction video
Synchronous stage — Live interviews
● Technical interview with our engineering team (scheduled at your convenience)
● Final interview with your future teammates
If it’s a match—you’ll get an offer!

Department/Project Description

Project aims to integrate a data-driven Markdown Optimization module and enhance Promotions Forecasting within clients' Price Index Management (PIM) to maximize gross profit, sell-through, and capture rate while maintaining price image. It will automate pricing recommendations based on inventory, generate accurate demand forecasts, and improve markdown/promotional strategies through user-friendly workflows.
GlobalLogic will develop the backend, data science, and UI/UX for this standalone application.

Job Responsibilities

• Build and maintain data pipelines adhering to the suggested enterprise architecture principles and guidelines
• Collect and manage data, converting it into useful information
• Work on the optimisation of partitioning and clustering for selected tables
• Implementation of data retention policies and removal of unused/dormand tables
• Work on the various optimisations
• Design, build, test, and maintain data management systems
• Work in sync with internal and external team members like data architects, data scientists, data analysts to handle all sorts of technical issue
• Deliver quality deliverables on time
• Translate complex functional requirements into technical solutions.

Job Description

• 5+ years of experience in Data Engineering
• Creation and maintenance of optimum data pipeline architecture for the ingestion and processing of data
• Creation of necessary infrastructure for ETL jobs from a wide range of data sources
• Experience in Snowflake cost optimisation, query pruning, and performance tuning
• Experience in Data storage technologies
• Upper Intermediate level of English
• Experience with GCP
• Good experience developing ETL pipeline using DBT
• Good Communication skills
• Willing to learn new technologies, share your ideas and assist other team members as needed
• Strong analytical and problem-solving skills; ability to define problems, collect data, establish facts, and draw conclusions

✨ About us   

code.store is a French software services company on a mission to enhance business operations by building smart, lean software. We use AI agents, low-code platforms, and SaaS tools to deliver solutions that are fast, efficient, and truly owned by our clients — no technical debt, no long-term dependencies.

We’re both a consulting partner and a delivery powerhouse. That means we don’t just build what clients ask for, we dig deep to understand how they work and how we can help them work better.

🏠 Offices

Our company is headquartered in Paris, yet our tech team operates remotely.

⚡Our Values

• Excel at what we do
• Provide the best technical and functional quality to our clients
• Kindness, honesty, fun, and trust
• Stay curious and always keep learning
   

✏️ Your responsibilities

• Own the end-to-end design and implementation of the Modern Data Stack in a highly fragmented and low-maturity environment
• Build a production-grade data foundation from scratch, ensuring reliability, scalability, and fast time-to-value
• Integrate and reconcile multiple data sources (CRM Batch, Piano, WordPress, analytics tools) into a single source of truth
• Design and implement a robust data warehouse architecture aligned with business-critical use cases
• Develop, optimize, and orchestrate resilient data pipelines (Airbyte, SQL, orchestration tools)
• Define and implement a Master Data Management approach (Golden Record / Master ID) across inconsistent data sources
• Take full ownership of data quality, including monitoring, validation, and continuous improvement processes
• Translate ambiguous business needs into clear, scalable data models (users, subscribers, interactions, churn signals)
• Deliver ready-to-use datasets for churn prediction, segmentation, and CRM activation under tight timelines
• Make and defend architecture and tooling decisions, balancing speed vs long-term sustainability
• Ensure data is actionable and accessible for data science, product, and business stakeholders
• Enable daily operational use cases (e.g., churn scoring, CRM automation) with high reliability
• Proactively communicate trade-offs, risks, and limitations to both technical and non-technical stakeholders

🎯 You’re the right candidate if you have

• 4+ years of hands-on experience in data engineering within Modern Data Stack environments
• 4+ years of deep experience with advanced SQL and data transformation at scale
• 4+ years of experience building robust, production-grade data pipelines (ETL/ELT)
• Proven experience with data warehouse architecture (BigQuery, Snowflake, Redshift, or equivalent)
• Strong understanding of data modeling (analytical & operational) and data system design
• Solid experience with data quality frameworks, MDM, and identity resolution in complex environments
• Practical understanding of business-driven use cases (churn, engagement, CRM, segmentation)
• Ability to work autonomously in low-structure, high-ambiguity environments
• Strong ownership mindset with a focus on delivering business impact, not just technical output
• English proficiency at B2 level or above
   

🧩 Will be a big plus

• Experience working in subscription-based businesses, digital media, or marketing-driven organizations
• Proven track record of building a data platform from scratch under time and resource constraints
• Hands-on experience with Airbyte, dbt, and modern orchestration tools
• Experience integrating with CRM and product analytics platforms (e.g., Batch, Piano, similar)
• Exposure to churn modeling pipelines, feature engineering, and production ML/data science workflows

💻 Tech stack on different projects

Backend: Xano (low-code back-end as a service, database, and API layer), NestJS, Node.js, TypeScript, TRPC

Frontend: Next.js, Custom React frontends (some Content Management Systems provide their own

🤝Hiring process

• 1h interview with HR and a technical prescreening in English. Please note that your answers will be recorded on video and shared with our tech team for further review
•  1.5h Technical interview 
• 30 min interview with CTO