Jobs Data & Analytics

Position Description:
As a Data Engineer, you will play a key role in designing and maintaining scalable data pipelines and platforms.
You’ll work closely with data scientists, analysts, and product teams to ensure high-quality, reliable, and scalable data is always available. This role requires deep technical expertise, strong analytical skills, and exposure to emerging AI/LLM technologies
Location(s): Germany & EU
Working Model: remote

Role Overview
As a Senior Data Engineer, you will play a key role in designing and maintaining scalable data pipelines and platforms. You’ll work closely with
data scientists, analysts, and product teams to ensure high-quality, reliable, and scalable data is always available. This role requires deep
technical expertise, strong analytical skills, and exposure to emerging AI/LLM technologies.

Key Responsibilities

• Design, develop, and optimize scalable data pipelines using Python and PySpark.
• Build, manage, and optimize big data solutions leveraging Google Cloud Platform (BigQuery, DataProc, Dataflow).
• Collaborate with cross-functional teams to translate business requirements into efficient data models and workflows.
• Ensure data accuracy, consistency, and availability across multiple systems and applications.
• Implement best practices for data governance, quality, and security.
• Stay updated with advancements in big data, cloud, and AI technologies, recommending innovative solutions.
• Mentor junior engineers and establish best practices within the team.

Requirements for "Professional Skills"
All professional skills required to fulfill the following general task description:
Works as a developer and is responsible for the development and programming of software, tools, systems, etc., as well as the associated troubleshooting and error analysis. This role requires comprehensive knowledge of various programming languages as well as appropriate development tools, methodologies, and development processes.

Works on the integration of systems, applications, or databases with one another or into other systems/software. This role requires exceptional knowledge of scripting and various programming languages, along with relevant integration tools, methods, and processes. It also requires a strong understanding of the technologies or systems being integrated.

Also works as an engineer and documents operational requirements in the form of system performance parameters and system configurations. He/she is additionally responsible for ensuring the seamless integration of architecture and development.

This also includes system integration or network integration activities, for example, SDM.

Projects using Agile development methodology:
If the contractor works within a Scrum team, they possess extensive knowledge of Scrum methodology and have experience in developing software within such a framework.

Requirements for "Social Skills"
All social skills required to fulfill the previously mentioned general task description as well as the following requirements:
The employee has intermediate-level experience, typically between 2 and 5 years, in their role or in the tasks performed by the group. Alternatively, the role and responsibilities require solid, but not exceptional, expertise.
The activities are associated with a moderate level of complexity and responsibility and require the ability to work independently.
The project may be carried out at either a national or international level.

Other Requirements & Relativizations
Skill Sets
Core Technical Skills

• Python (expert-level coding, modular programming, debugging, performance optimization)
• PySpark (distributed processing, tuning, handling large-scale data, performance optimization)
• Google Cloud Platform (GCP):
• BigQuery – advanced SQL, optimization, partitioning, clustering, cost management
• DataProc – Spark/Hadoop cluster management, job orchestration
• Dataflow – streaming & batch pipelines, real-time processing

Big Data & Cloud Skills

• Strong understanding of big data technologies (distributed computing, Hadoop/Spark ecosystem, data lakes, Kafka, batch & stream processing)
• Experience with data modeling and designing scalable data pipelines
• Familiarity with cloud-native architectures and serverless processing
•  

Analytical & Problem-Solving Skills:

• Ability to analyze complex data sets and derive insights
• Strong logical and critical thinking
• Experience optimizing query performance and pipeline efficiency
• Comfortable troubleshooting large-scale data workflows
• Preferred / Nice-to-Have Skills
• Experience with CI/CD pipelines for data engineering workflows
• Workflow orchestration: Airflow, Cloud Composer, Dagster
• Data governance, data quality frameworks, and compliance standards
• AI & Advanced Analytics Exposure
• Familiarity with Large Language Models (LLMs) and their applications in data workflows
• General understanding of AI/ML concepts and how they integrate with data engineering pipelines
• Exposure to MLOps tools or frameworks for deploying and monitoring AI models

Soft Skills

• Strong communication and collaboration with cross-functional teams
• Ability to work in Agile environments
• Mentoring and guiding junior engineers
• Self-driven, proactive learner, and adaptable to emerging technologies

We are looking for a strong Middle Backend Engineer to help us build AI-powered products and workflows. This role is ideal for someone with solid Node.js / TypeScript experience who is already exploring AI in practice and wants to go deeper into RAG, voice agents, and multi-agent systems.

What matters most is a strong backend foundation, the ability to build reliable production systems, and a genuine interest in how LLM-based applications work and in using AI to speed up delivery.

What you’ll do

• Design and build backend services for AI-powered product features
• Work with LLM APIs, prompts, AI SDKs, and agent workflows
• Help shape systems involving retrieval, grounding, tool use, and orchestration
• Collaborate on products that include Node.js backend 
• Improve reliability, latency, observability, and overall production readiness of AI features

• Explore and implement capabilities around RAG, voice experiences, and multi-agent systems

   

What we’re looking for

• Strong commercial experience with Node.js / TypeScript, 2+ years of experience
• Experience building and maintaining complex backend systems in production
• Solid understanding of architecture, APIs, async flows, integrations, and system reliability
• Some hands-on exposure to LLM applications: prompt design, AI APIs, agent flows, or internal AI tooling
• Ability to learn quickly in a fast-moving technical area
• Strong engineering judgment and product mindset

• A degree in Computer Science, Mathematics, or a related field is a plus, but not required

   

Nice to have

• Experience with LangChain, LangGraph, Vercel AI SDK, or similar frameworks
• Familiarity with RAG concepts such as chunking, embeddings, retrieval, reranking, and hallucination reduction
• Experience with voice agents or real-time AI experiences
• Experience with React

• Familiarity with Python

   

Why this role

• You’ll work on real AI product problems, not toy demos
• You’ll have room to grow into RAG and agentic systems
• We’re open to hiring a strong engineer with the right mindset, even if some of the AI-specific depth is still developing

About the Client

Our client is the world’s largest human resources consulting firm, headquartered in New York City, with major operations across more than 40 countries.

The organisation employs more than 25,000 professionals globally and delivers services across 130+ countries, supporting some of the world's largest enterprises. Its solutions and expertise are trusted by 97% of Fortune 500 companies.

About the Role

We are looking for experienced Forward Deployed Engineers to design, build, and maintain reusable Claude Code Skills that enable AI agents to support complex software-development and business workflows.

You will work directly with business stakeholders and domain experts to understand their objectives, processes, constraints, and operational knowledge, and translate these inputs into reliable, reusable AI capabilities.

This is a highly hands-on engineering role at the intersection of software engineering, AI agent development, prompt engineering, context engineering, and business process automation.

Key Responsibilities

• Work directly with business stakeholders and domain experts to understand their objectives, workflows, constraints, and expected outcomes.
• Analyse business requirements, documentation, examples, templates, and other reference materials to identify opportunities for AI-driven automation.
• Identify business workflows and use cases that can be implemented, streamlined, or enhanced through Claude Code Skills.
• Design, implement, test, and maintain reusable and production-quality Claude Code Skills.
• Develop clear skill instructions, supporting scripts, reference materials, validation logic, and reusable workflow components.
• Translate complex, ambiguous, or domain-specific business processes into structured and executable instructions for AI agents.
• Apply prompt and context engineering techniques to improve the reliability and effectiveness of AI-driven workflows.
• Evaluate skill behaviour using realistic scenarios, test cases, acceptance criteria, and representative business data.
• Iteratively improve the accuracy, reliability, usability, and maintainability of AI skills based on testing results and stakeholder feedback.
• Collaborate with engineering and business teams to ensure developed solutions are practical, scalable, and aligned with real-world requirements.
• Contribute to the development of reusable patterns and best practices for agentic engineering and AI-powered developer workflows.

Required Experience

• Strong hands-on experience using Claude Code in real-world software development or business workflow scenarios.
• Practical experience creating Claude Code Skills or comparable reusable capabilities for AI coding agents.
• Strong understanding of modern AI engineering and agentic development patterns, including:
• Agentic workflows
• Tool use and tool calling
• Prompt engineering
• Context engineering
• Structured instruction design
• AI workflow orchestration
• Proven professional software engineering experience, with the ability to design, build, test, review, and maintain production-quality solutions.
• Ability to translate business requirements, operational processes, and domain knowledge into clear technical designs and executable AI workflows.
• Experience working with non-deterministic AI systems, including evaluating behaviour, identifying failure modes, and iteratively improving solution quality.
• Strong analytical and problem-solving skills, with the ability to work effectively in ambiguous and rapidly evolving environments.
• Strong communication skills and the ability to collaborate directly with both technical and non-technical stakeholders.

Nice to Have

Advanced hands-on experience with Claude Code, particularly authoring:

• Claude Code Skills
• Plugins
• MCP server
  Experience with LLM evaluation and testing frameworks, such as:
• Promptfoo
• LangSmith
• Custom evaluation harnesses

We are the creators of a new fintech era!
Our mission is to change this world by making blockchain accessible to everyone in everyday life. WhiteBIT is a global team of over 1,200 professionals united by one mission — to shape the new world order in the Web3 era. Each of our employees is fully engaged in this transformative journey.
We work on our blockchain platform, providing maximum transparency and security for more than 8 million users worldwide. Our breakthrough solutions, incredible speed of adaptation to market challenges, and technological superiority are the strengths that take us beyond ordinary companies. Our official partners include the National Football Team of Ukraine, FC Barcelona, Lifecell, FACEIT and VISA.


The future of Web3 starts with you: join us as a Product Analyst!

Requirements

— 5+ years in product analytics, preferably in fintech, payments, or banking products;
— Advanced SQL skills; confident working with large raw datasets from backend sources;
— Hands-on experience with PostHog — event tracking, funnel and retention analysis, feature flags analytics;
— Proficiency in Tableau — building production-grade dashboards consumed by non-technical stakeholders;
— Experience with BigQuery / Snowflake / Redshift as primary data warehouse;
— Working knowledge of dbt — understanding models, lineage, and writing/modifying transformations;
— Python / pandas for data wrangling, ad-hoc analysis, and automation of repetitive analytical tasks;
— Solid understanding of payments flows (authorization, settlement, chargebacks), conversion funnels, cohort analysis, and fraud/risk metrics;
— Ability to independently scope analytical requests, challenge vague questions, and deliver structured insigh — not just charts;
— Experience working in cross-functional teams with Product, Growth, and Risk stakeholders;
— English B2+ for documentation and async communication;

Responsibilities

◇ Analytics delivery:
— Own end-to-end analytics across user funnels, payments, risk & fraud, and growth - from request intake to insight delivery;
— Answer complex business questions using SQL queries against BigQuery/Snowflake/Redshift, dbt models, and PostHog event data;
— Build and maintain Tableau dashboards actively used by Product, Growth, and Risk teams;
— Conduct funnel, cohort, retention, and segmentation analysis to support product decisions;

◇ Collaboration:
— Work closely with Product Managers to define metrics, instrument new features in PostHog, and evaluate product performance post-release;
— Partner with the Growth & Marketing team on acquisition funnel analysis, campaign attribution, and conversion optimization;
— Support the Risk & Fraud team with behavioral pattern analysis, anomaly detection, and monitoring of fraud signals;
— Align with backend engineers on data availability, event schemas, and data quality issuesp;

◇ Proactive & structural work:
— Audit current analytical coverage and identify gaps in instrumentation or reporting;
— Propose and implement automation and self-serve solutions to reduce the volume of repetitive ad-hoc requests;
— Contribute to dbt models - write new transformations and improve existing ones as needed;
— Document analytical approaches, metric definitions, and dashboard logic to build team knowledge base;

Good to have

— Prior experience in a high-request-volume environment with a structured intake process;
— Exposure to fraud detection models or risk scoring logic;
— Experience building self-serve analytics layers to reduce ad-hoc load;

Work conditions

— Master cutting-edge technologies and become an expert in the most innovative industry;
— Work with the Fintech of the Future: develop your skills in digital finance and shape the global market;
— Take Your Professionalism to the Next Level: gain unique experience and be part of global transformations;
— Drive Innovations: influence the industry and contribute to groundbreaking solutions;
— Join a Strong Team: collaborate with top experts worldwide and grow alongside the best;

Work-Life Balance & Well-being:
— Modern equipment;
— Comfortable working conditions, and an inspiring environment to help you thrive;
— 24 calendar days of paid leave;
— Additional days off for national holidays.

Description

The engagement supports a maintenance assessment and advisory for a legacy environment, running mission-critical batch and online workloads. The objective is to establish a fact-based understanding of the current application estate and its support model, and to define a scoped, low risk maintenance pilot as the basis for a potential longer term managed services engagement.

The initial advisory phase is an assessment structured in three stages: a scope-alignment workshop to agree services, ownership, and boundaries; a current-state assessment of the code estate, data, batch/online flows, operations, and ticket history to establish baselines and pain points; and a pilot-identification stage to prioritize candidate use cases and define objectives and success metrics. The phase is diagnostic in nature — it covers evaluation, characterization, and effort estimation only, with no code remediation or production changes performed during assessment. Success depends heavily on timely access to client subject-matter experts and to the target environment.

Requirements

• Proven ability to elicit and document business rules embedded in legacy applications.
• Experience analysing incident/ticket history to establish operational baselines and pain points.
• Skilled at facilitating functional discovery workshops with mixed business and technical stakeholders.
• Able to define and baseline SLAs, KPIs, and success metrics for a support engagement.
• Comfortable using AI tooling to accelerate analysis while verifying outputs against source data.

• Work on legacy or mission-critical systems.

   

Job responsibilities

• Lead functional discovery workshops to map what the financial applications do from a business perspective.
• Document critical business rules, batch dependencies, and functional pain points tied to legacy code.
• Analyse incident and backlog history, using AI-assisted clustering where useful, to establish a current-state support baseline.
• Define SLA, KPI, and success-metric baselines for the proposed maintenance model.
• Triage and prioritize candidate use cases for the maintenance pilot by business impact.
• Consolidate current-state findings into the assessment deliverables alongside the architect.]

What we offer

Empowering Projects: With 500+ clients spanning diverse industries and domains, we provide an exciting opportunity to contribute to groundbreaking projects that leverage cutting-edge technologies. As a team, we engineer digital products that positively impact people’s lives.

Empowering Growth: We foster a culture of continuous learning and professional development. Our dedication is to provide timely and comprehensive assistance for every consultant through our dedicated Learning & Development team, ensuring their continuous growth and success.

DE&I Matters: At GlobalLogic, we deeply value and embrace diversity. We are dedicated to providing equal opportunities for all individuals, fostering an inclusive and empowering work environment.

Career Development: Our corporate culture places a strong emphasis on career development, offering abundant opportunities for growth. Regular interactions with our teams ensure their engagement, motivation, and recognition. We empower our team members to pursue their career goals with confidence and enthusiasm.

Comprehensive Benefits: In addition to equitable compensation, we provide a comprehensive benefits package that prioritizes the overall well-being of our consultants. We genuinely care about their health and strive to create a positive work environment.

Flexible Opportunities: At GlobalLogic, we prioritize work-life balance by offering flexible opportunities tailored to your lifestyle. Explore relocation and rotation options for diverse cultural and professional experiences in different countries with our company.

About the Role

Our client is a global fintech company and one of the world's leading platforms for financial analytics and investment insights. They are looking for a Senior Data Analyst to help drive product decisions through data and uncover actionable insights from user behavior across web and mobile platforms.

Responsibilities

• Analyze user behavior and product performance using raw data.
• Define, track, and optimize key product KPIs.
• Build dashboards and perform deep-dive analyses to support business decisions.
• Design, monitor, and evaluate A/B tests.
• Analyze and improve key metrics, including Conversion, Retention, Churn, Engagement, and Revenue.
• Partner with Product, Engineering, and Business teams to deliver data-driven recommendations.

Requirements

• 5+ years of experience as a Data Analyst in a B2C product environment.
• Advanced SQL skills with experience writing complex analytical queries.
• Hands-on experience with BI tools such as Looker, Tableau, or Power BI.
• Strong understanding of product analytics, web/mobile user behavior, and A/B testing.
• Excellent analytical and problem-solving skills.
• Upper-Intermediate (B2+) or higher level of English.

Senior Data Modelling Analyst

Designs and maintains the data models that underpin analytics and BI reporting, working closely with business stakeholders and data engineers to make sure data structures accurately represent business processes and support reliable, consistent reporting.

Key Responsibilities:

• Design conceptual, logical, and physical data models to support analytics and BI reporting
• Translate business requirements into scalable, well-documented data models
• Define and maintain dimensional models (star/snowflake schemas) for data warehouses
• Partner with data engineers to ensure models are implemented correctly in production
• Maintain data dictionaries, model documentation, and naming standards
• Review and validate data models for consistency, performance, and scalability
• Support ad hoc data analysis and modeling requests from business stakeholders

Requirements:

• 5+ years of experience in data modeling (conceptual, logical, physical)
• Strong expertise in dimensional modeling (star/snowflake schemas) for data warehouses
• Experience translating business requirements into data model design
• Proficiency in SQL and data modeling tools (e.g., ERwin, dbt, Lucidchart)
• Strong understanding of data warehousing concepts and BI/reporting needs
• Strong communication skills to work across business and engineering teams
• Experience maintaining data dictionaries and documentation standards

Nice to Have:

• Experience with a modern cloud data warehouse (Snowflake, Redshift, Synapse, BigQuery)
• Familiarity with BI tools (Power BI, Tableau, Looker)
• Background working in a consulting or client-facing environment

We're looking for a Computer Vision Engineer to build visual intelligence features for a product that runs across connected devices and mobile apps.

This is a hands-on engineering role, not a research one: you'll take CV models from training to production, with a strong focus on making them run fast on resource-constrained devices.

What you'll do:

• Design, train, and deploy CV models - object detection, classification, segmentation, visual analysis;
• Optimize models for edge and mobile inference (quantization, pruning, distillation);
• Build data pipelines for image and video processing, including annotation and dataset versioning;
• Set up monitoring and retraining workflows for models in production;
• Work with backend and mobile teams to integrate model outputs into user-facing features.

Requirements:

• 3+ years in applied computer vision or ML with a strong CV focus;
• Solid deep learning background: CNNs, detection and segmentation architectures (YOLO, Faster R-CNN, U-Net), vision transformers;
• Python, PyTorch or TensorFlow, OpenCV;
• Experience deploying and maintaining CV models in production;
• Hands-on with on-device inference: ONNX, TensorRT, TensorFlow Lite, Core ML, or OpenVINO;
• Cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• English: Intermediate or higher.

Nice to have:

• MLOps tools (MLflow, Airflow, Vertex AI);
• Real-time video processing at scale (FFmpeg, GStreamer, Kafka);
• Edge AI or mobile ML experience.

Designs and maintains the data models that underpin analytics and BI reporting, working closely with business stakeholders and data engineers to make sure data structures accurately represent business processes and support reliable, consistent reporting.

Key Responsibilities:

• Design conceptual, logical, and physical data models to support analytics and BI reporting
• Translate business requirements into scalable, well-documented data models
• Define and maintain dimensional models (star/snowflake schemas) for data warehouses
• Partner with data engineers to ensure models are implemented correctly in production
• Maintain data dictionaries, model documentation, and naming standards
• Review and validate data models for consistency, performance, and scalability
• Support ad hoc data analysis and modeling requests from business stakeholders

Requirements:

• 5+ years of experience in data modeling (conceptual, logical, physical)
• Strong expertise in dimensional modeling (star/snowflake schemas) for data warehouses
• Experience translating business requirements into data model design
• Proficiency in SQL and data modeling tools (e.g., ERwin, dbt, Lucidchart)
• Strong understanding of data warehousing concepts and BI/reporting needs
• Strong communication skills to work across business and engineering teams
• Experience maintaining data dictionaries and documentation standards

Nice to Have:

• Experience with a modern cloud data warehouse (Snowflake, Redshift, Synapse, BigQuery)
• Familiarity with BI tools (Power BI, Tableau, Looker)
• Background working in a consulting or client-facing environment

Readdle is a pioneering force in the personal productivity space on Apple devices, having shaped the landscape since 2007. Our mission is to empower individuals and teams with innovative technology, enhancing their efficiency and creativity. We are dedicated to crafting exceptional mobile and desktop experiences for those who aspire to achieve more.
 

As a Senior Growth Analyst at Readdle, you’ll own the numbers behind how Spark grows. From the first ad impression to long-term renewals, you’ll make sense of the data, design event structures, and ensure everything is measurable. You’ll dig into funnels, uncover insights, and build dashboards that make growth performance crystal clear for product and marketing teams.

What will you do:

• Transform and analyze large datasets in BigQuery and Amplitude to uncover trends, anomalies, and actionable insights across the user journey.
• Build and maintain self-serve dashboards in Tableau and Google Sheets that reduce ad-hoc reporting requests and establish a clear source-of-truth for growth metrics.
• Define, document, and QA event structures for new features, campaigns, and experiments; build a robust monetization measurement system to support pricing and migration decisions.
• Analyze user funnels across ads, store, onboarding, in-app usage, purchases, and cancellations to identify drop-offs and growth opportunities.
• Design and monitor A/B experiments and feature launches; validate results and ensure long-term impact tracking.
• Proactively surface insights, hypotheses, and growth opportunities to marketing and product teams; shape quarterly prioritization with impact scenarios to influence roadmap decisions.
• Build forecasting and scenario models for installs, conversions, retention, and revenue.
• Ensure data integrity across tools and pipelines through established QA processes; work with Appsflyer to track attribution and optimize acquisition reporting.

About you:

• 5+ years in growth, product, or marketing analytics in a B2C or SaaS environment, with experience supporting pricing, monetization, or migration initiatives in subscription-based products.
• Strong SQL skills and experience with BigQuery or similar cloud data warehouses (Redshift, Snowflake); proficiency in Tableau and/or Amplitude for dashboards and complex data visualization.
• Experience with Appsflyer or other attribution platforms; familiarity with Python for data analysis and automation is a strong plus.
• Solid understanding of product analytics (funnels, cohorts, retention, event tracking), statistics, A/B testing, and concepts like segmentation, churn, or LTV modeling.
• Proven ability to design self-serve dashboards and act as a strategic thought partner to PM/PMM teams, not just an executor of analytics requests.
• Comfortable working cross-functionally with product, marketing, and engineering teams with a proactive, curious, and coachable mindset.

What you will get at Readdle:

• Customer-centric culture. We put our users at the heart of everything we do. Every team member has the opportunity to engage directly with customers, gaining insights that shape meaningful, delightful experiences for millions worldwide.
• Relentless growth. We’re committed to mastery in our craft. We take ownership of our work, decisions, and outcomes, and we see feedback as a catalyst for growth. Every challenge is an opportunity to learn, evolve, and raise the bar.
• Exceptional people, exceptional team. Our greatest strength is our people. We care deeply about each other, work transparently, and celebrate collective success. Together, we build an environment where everyone can do their best work and grow beyond their potential.
• Real impact. We design products that truly matter. Our focus is on delivering tangible value, simplifying complexity, pushing boundaries, and continuously improving how we build and deliver solutions to our users.
• Culture of innovation. We embrace curiosity and creativity in everything we do. Fresh ideas are not just welcomed, they’re expected, celebrated, and turned into real innovations that shape the future of our products and company.

A second hands-on senior engineering role alongside Senior Data Engineer #1, building and maintaining production data pipelines on one cloud platform — typically covering a different workstream or cloud stack within the same data engineering team.

Key Responsibilities:

• Design, build, and maintain scalable ETL/ELT pipelines on AWS or Azure
• Optimize pipeline performance, reliability, and cost-efficiency
• Implement data-quality checks, monitoring, and alerting for production pipelines
• Collaborate with the Data Engineering Lead and Architect on pipeline design and standards
• Support data modeling and schema design together with the Data Modelling Analyst
• Troubleshoot and resolve data pipeline issues in production
• Participate in code reviews and contribute to engineering best practices

Requirements:

• 5+ years of hands-on data engineering experience
• Deep expertise in one cloud platform: AWS (Glue, S3, Redshift, EMR, Lambda, Kinesis) or Azure (Data Factory, Synapse, ADLS, Databricks)
• Strong SQL and Python (or Scala) skills; experience with orchestration tools (Airflow, ADF, etc.)
• Experience with ETL/ELT design, data-quality checks, and performance optimization
• Familiarity with distributed data processing frameworks (Spark)
• Experience operating production data pipelines at scale
• Solid understanding of data warehousing and dimensional modeling concepts

Nice to Have:

• Familiarity with CI/CD and infrastructure-as-code (Terraform)
• Experience with streaming data pipelines (Kafka, Kinesis, Event Hubs)
• Exposure to dbt or similar transformation tooling

Leads a team of data engineers delivering pipelines and platform components across AWS and Azure, balancing hands-on technical work with people leadership. Partners with the Data Architect and business stakeholders to keep the team's roadmap aligned with platform architecture and delivery priorities.

Key Responsibilities:

• Lead and mentor a team of data engineers delivering pipelines across AWS and Azure
• Own technical design and implementation decisions for data pipeline architecture
• Establish and enforce engineering best practices: code quality, testing, CI/CD, documentation
• Plan and prioritize the team's roadmap in collaboration with architecture and business stakeholders
• Troubleshoot and resolve complex data pipeline and platform issues
• Drive adoption of orchestration, monitoring, and data-quality tooling
• Partner with the Data Architect to keep delivered pipelines aligned with platform architecture

Requirements:

• 7+ years of data engineering experience, including 2+ years in a technical leadership role
• Hands-on expertise with both AWS (Glue, EMR, Redshift, Lambda, Kinesis) and Azure (Data Factory, Synapse, Databricks)
• Strong background in pipeline architecture, orchestration (Airflow/ADF), and CI/CD for data
• Experience mentoring engineers and setting technical best practices across a team
• Solid SQL and Python/Scala skills, with experience in distributed data processing (Spark)
• Experience with data quality, testing, and monitoring frameworks
• Strong communication and planning skills; comfortable working directly with stakeholders

Nice to Have:

• Experience with dbt or similar transformation frameworks
• Familiarity with infrastructure-as-code (Terraform, CloudFormation, Bicep)
• Prior experience in a consulting or client-facing delivery environment

AI Delivery Engineer  —  Agent Tooling & Code Generation

Builds and ships production-grade AI agent tooling and code-generation solutions, working closely with engineering and product teams to embed AI agents into the delivery lifecycle — from prototyping through reliable, monitored production rollout.

Key Responsibilities:

• Design, build, and maintain AI agent tooling that automates engineering and business workflows
• Develop and refine code-generation pipelines and developer copilots
• Integrate LLM APIs and agent-orchestration frameworks into production systems
• Build and maintain RAG pipelines, vector stores, and prompt-engineering workflows
• Identify high-value automation opportunities together with engineering and product teams
• Monitor, evaluate, and improve agent performance, reliability, and safety in production
• Document tooling and support internal teams adopting AI agents

Requirements:

• 4+ years of software engineering experience, with recent focus on applied AI/LLM systems
• Hands-on experience building LLM-based agents or agent-orchestration frameworks (e.g., LangChain, LangGraph, AutoGen, or custom pipelines)
• Experience with code-generation tooling, developer copilots, or AI-assisted development workflows
• Strong Python skills (TypeScript/JS a plus) for building agent tooling and integrations
• Experience with LLM APIs (OpenAI, Anthropic, etc.), RAG pipelines, and vector databases
• Proven ability to take AI prototypes from concept to reliable, production-grade delivery
• Understanding of prompt engineering, evaluation, and guardrails for LLM-based systems

Nice to Have:

• Experience deploying agentic frameworks in enterprise settings
• Familiarity with MLOps/LLMOps practices
• Contributions to open-source AI tooling

About the Role

We are looking for a mature Product / Data Analyst who will become the absolute owner of our data tracking and analytics ecosystem.

This is a "Greenfield" opportunity to build analytics layer for Big Data B2B SaaS product  while extracting deep mathematical insights from raw Big Data to optimize our retargeting algorithms.

Responsibilities

• Build BI Infrastructure from Scratch: Evaluate and select the optimal BI tool (Looker Studio, Grafana, Apache Superset, or Metabase) over our ClickHouse database to eliminate manual report-building.
• Behavioral & Touchpoint Analysis: Model Path to Conversion, optimize Frequency Caps, and run Recency & Frequency analysis to find "golden hours" and maximize conversion probability.
• Incrementality & Attribution: Mathematically prove incremental GGR uplift and measure the indirect impact of ad contacts (post-view effects) through control groups.
• Data Quality & Logging: Control metadata collection integrity (IP, User-Agent, Device ID) and formulate requirements for logging new data points.
• Big Data & Query Optimization: Independently write and optimize complex SQL queries in ClickHouse to process billions of raw events without relying on the engineering team.
• Product Insights: Utilize Python for cohort analysis, target audience segmentation in a Cookieless environment, and pattern detection for anti-fraud.

Who We’re Looking For

We’re looking for a mature, self-driven analyst who loves data engineering challenges, possesses strong mathematical logic, and can translate raw numbers into business impact.

Must-have:

• 3+ years of commercial experience in data/product analytics working with Big Data.
• Strong domain expertise: Experience in high-load industries such as AdTech, RTB, MarTech, or iGaming.
• Advanced SQL (ClickHouse): Deep understanding of column-oriented databases and raw log processing.
• Python Proficiency: Strong practical experience with Pandas and NumPy for complex cohort and statistical analysis.
• Data Visualization Mastery: Confident experience designing and connecting BI dashboards completely from scratch.
• English: Intermediate or higher (comfortable reading technical documentation and product contexts).
• Ukrainian/Russian: Fluent (for internal team communication).

Nice to have:

• Academic background in Mathematics, Statistics, Data Analysis, or Probability Theory.
• Experience in anti-fraud traffic analytics.
• Understanding of subscription models and LTV forecasting.

How We Work

• Direct reporting line to the Product Owner / CEO.
• Focus on automated, long-term infrastructure over routine daily manual exports.
• Full autonomy in selecting data-analysis tools.
• Clear boundaries: The analyst does not manage ad campaigns manually and does not act as a database administrator (DBA).

What We Offer

• Full ownership over the company's data architecture and reporting standards.
• A highly complex, high-load product dealing with billions of events.
• Competitive compensation.
• 100% remote format with international market exposure.

Role Summary

The Product / Data Analyst is responsible for transforming raw ClickHouse logs into a transparent, automated BI ecosystem while delivering mathematically sound insights to boost the platform's retargeting efficiency.

About the Company
Sales'Up is a leading Creatio implementation partner, helping enterprise clients across FMCG, Agro, Finance and Pharma transform their business processes. Over 8+ years, we've delivered 100+ successful CRM projects and built our own industry-specific products: Data Management, FMCG Management, and Agro Management — used by market leaders. We're a team of 50+ professionals, growing fast and building a culture where modern AI tools are part of everyday work. Join us to work on complex, real-world enterprise challenges and grow together!

Role
We are looking for a Middle/Senior Business Analyst to join our team and work at the intersection of business needs and technical solutions. You'll run discovery sessions directly with enterprise clients, translate their real business problems into clear, actionable requirements, and see your analysis shape solutions used by market leaders in FMCG, Agro and Finance.

Main Responsibilities

• Learning the company's products and their configuration
• Requirement gathering: identifying client needs and expectations, analyzing their business processes
• Analysis and documentation: developing documentation that describes functional and technical requirements for the system
• Defining technical solutions: collaborating with technical specialists to develop and choose optimal solutions
• Project coordination: ensuring communication between the development team and the client, tracking project progress
• Testing and validation: verifying CRM system compliance with requirements and validating the finished product with the client
• User training: organizing and conducting training for end users
• Support and improvement: post-implementation consulting support, results analysis, and improvement proposals
• Presenting developed solutions to the client

Requirements

Experience & Education

• 3+ years of experience as a Business Analyst in IT
• Experience on CRM projects (Creatio, Salesforce, Microsoft Dynamics, SAP CRM, etc.) — significant advantage

CRM & Business Process Knowledge

• Understanding of CRM system logic: sales funnel, sales pipeline, customer journey, case management
• Experience in business process analysis and modeling (BPMN — required)
• Understanding of industry specifics — a plus

Documentation & Artifacts

• Experience preparing FRD, User Stories, Use Case Specifications
• Experience conducting gap analysis (comparing requirements against existing functionality/estimates)
• Ability to prepare technical specifications clear to both the client and the development team

Communication & Soft Skills

• Experience conducting discovery sessions and client interviews
• Ability to structure and document discovery call outcomes (pain points, requirements)
• Fluent spoken and written Ukrainian, confident technical English (Upper-Intermediate or higher)
• Ability to present solutions and defend the analytical position in front of the client
• Experience conducting end-user training

Technical Skills

• Understanding of CRM integration principles with adjacent systems (ERP, accounting systems)
• Basic understanding of the no-code/low-code approach to business logic customization

AI Tools in Analyst Work

• Experience with or willingness to actively use Claude (and other AI tools) to accelerate analytical work: drafting FRD/User Stories, analyzing discovery call transcripts, gap analysis, preparing estimates
• Ability to write clear, effective prompts to get quality, structured output
• Critical thinking when working with AI-generated content — fact-checking and adapting it to the project's and industry's context

Domain Knowledge (will be a plus)

General CRM Domains (advantage)

• Understanding of the sales cycle: lead generation, qualification, sales funnel, opportunity management, sales forecasting
• Understanding of customer service/support processes: case management, SLA, omnichannel
• Basic understanding of marketing automation: segmentation, email/SMS campaigns, lead scoring
• Understanding of document flow and approval processes (workflow, approval processes)

Industry Expertise (advantage)

• Agri-trading: contracting specifics, pricing, supply logistics, working with elevators/counterparties
• Retail / Distribution: assortment matrix, distributor network management, discount and promo management, logistics and warehouse accounting
• Banking / financial services: compliance requirements, scoring processes, credit application handling (a plus, if applicable)

We Offer

• Competitive salary
• Professional development through internal and external training programs
• Transparent model of professional and career growth
• Option to work in the office or remotely
• 24 days of paid vacation
• English language courses