Jobs Data Engineer

About the Role

We are looking for a Senior Data Engineer to help design and scale our data platform that powers analytics, intelligent systems, and data-driven decision making.

You will work on building reliable data pipelines, designing scalable storage systems, and ensuring high-quality structured data across multiple sources. This role requires strong engineering fundamentals and experience working with modern data infrastructure.

You will collaborate closely with backend engineers, ML engineers, and product teams to ensure data is accessible, reliable, and ready for advanced analytics and AI use cases.

Responsibilities

• Design and maintain scalable data ingestion and processing pipelines
• Build and improve backend services responsible for data collection, transformation, and delivery
• Design and optimize PostgreSQL / time-series databases for analytical workloads
• Ensure data quality, consistency, and reliability across systems
• Implement monitoring, alerting, and recovery mechanisms for data pipelines
• Contribute to data architecture decisions and schema design
• Work with engineering teams to expose clean internal APIs for data access
• Improve performance, scalability, and maintainability of the data platform

Requirements

• 3+ years of professional experience in Python
• Strong experience with PostgreSQL and SQL optimization
• Experience designing data pipelines or ETL/ELT systems
• Familiarity with asynchronous processing or event-driven systems
• Experience working with message queues or streaming systems
• Solid understanding of data modeling and data architecture
• Experience with Docker-based development environments

Nice to Have

• Experience with time-series databases
• Experience with high-volume data pipelines
• Familiarity with distributed systems
• Experience working in data-heavy or analytics-driven products
• Experience with Kubernetes-based deployments

Tech Stack

Python · PostgreSQL · Redis · Message Queues · Docker · Kubernetes · CI/CD

We are looking for a Web Infrastructure & Cloudflare Specialist to support and maintain the technical foundation of our web projects in the iGaming / affiliate marketing space.

This role is focused on domain infrastructure, website availability, Cloudflare setup, and basic web security. You will work closely with marketing and product teams to ensure that our websites, mirrors, and landing pages remain stable, secure, and accessible.

Responsibilities

• Manage the domain infrastructure across multiple projects
• Configure and maintain Cloudflare settings, including:
  • DNS
  • CDN
  • WAF
  • SSL
  • security and firewall rules
• Set up and support website mirrors and domain rotation
• Monitor website availability and respond quickly to downtime or blocking issues
• Manage domains through registrars such as GoDaddy, Namecheap, and similar platforms
• Implement and maintain basic website protection, including anti-DDoS and firewall rules
• Create and support simple websites and pre-landing pages using WordPress or similar CMS platforms
• Handle basic technical SEO setup, including:
  • meta tags
  • robots.txt
  • sitemap
  • canonical tags
• Support the technical infrastructure of affiliate and marketing websites

Requirements

• Hands-on experience with Cloudflare
  • DNS
  • WAF
  • SSL
  • caching
  • security settings
• Solid understanding of domain infrastructure and DNS
• Experience managing multiple domains and website mirrors
• Experience building and maintaining websites via CMS platforms such as WordPress
• Basic understanding of technical SEO
• Understanding of website security and protection practices
• Ability to work with hosting providers and VPS environments

Nice to Have

• Experience in iGaming, affiliate, or betting projects
• Experience with Cloudflare advanced security features and anti-bot rules
• Experience with server infrastructure, including Linux and Nginx
• Experience with large-scale domain management

Role Overview

In this position, you will be responsible for:

• ensuring the stability and availability of websites
• managing domain infrastructure
• maintaining basic web security
• providing technical support for pre-landing pages and affiliate websites

GR8 Tech builds B2B iGaming platforms for operators who play to lead.

We deliver full-cycle, high-impact tech designed to scale — from seamless integrations and expert consulting to long-term operational support. Our platform powers millions of active players and drives real business growth. Call it what it is: the iGaming Platform for Champions.

With 1000+ GR8 people across locations and time zones, we don’t just ship technology — we help operators build success stories across brands, markets, and geos.

Our ambition drives us. Our people make it real.

If you’re a challenger in spirit and a champion in action — join us.

Why this role exists:

We’re looking for a Senior Data Engineer to design and operate a scalable data infrastructure powering a high-throughput, production-grade platform.

You will own data systems that support analytics, operational workloads, and ML-driven capabilities across a multi-tenant environment. This is a hands-on senior role with architectural responsibility and end-to-end ownership under strict reliability, performance, and SLA requirements.

You will influence core data architecture decisions and help evolve the platform to support growing scale and complexity.

What you’ll drive:

Core Responsibilities

• Design and operate batch and streaming data pipelines.
• Architect and evolve data storage layers (lake, analytical, operational).
• Develop scalable data models for analytics, ML, and operational systems.
• Ensure data quality, consistency, and observability across pipelines.

Platform & Reliability

• Implement real-time processing using event-driven architectures.
• Build ingestion and transformation workflows (ETL/ELT).
• Own backfills, reprocessing strategies, and data migrations.
• Implement CI/CD, monitoring, and SLA-driven operational practices.

Collaboration

• Partner with engineers, analysts, and data scientists to design reliable and scalable data solutions.
• Contribute to data platform standards and best practices.

Technical Environment

• Core: Python, SQL
• Streaming: Kafka
• Storage: PostgreSQL, Redis (ElastiCache), S3
• Analytics: AWS Athena, Starrocks
• Vector: PostgreSQL + pgvector
• Infrastructure: AWS, batch orchestration

What makes you a GR8 fit:

Must-have

• 5+ years of experience building and operating production-grade data systems under SLA constraints.
• Strong proficiency in SQL and Python.
• Hands-on experience with streaming systems (Kafka or similar).
• Experience with batch processing and workflow orchestration.
• Production experience with relational databases (PostgreSQL or similar), including performance tuning, indexing, and partitioning.
• Experience designing high-throughput and low-latency systems.
• Solid understanding of point-in-time correctness and reproducible data pipelines.
• Experience with caching systems (Redis or similar).
• Cloud experience (AWS preferred).
• Experience with analytical engines (Athena, StarRocks, ClickHouse, or similar).
• Experience with distributed processing frameworks (Spark, Flink, Beam, or similar).
• Experience implementing data quality frameworks and CI/CD for data pipelines.

Familiarity with vector databases or columnar storage systems.

Nice-to-have

• Experience supporting ML workloads (e.g., feature pipelines or feature storage patterns).
• Familiarity with training-serving consistency concepts.
• Experience building shared data platform components.
• Experience building lightweight data-serving APIs (e.g., FastAPI).
• Experience working with containerized environments (e.g., Docker).

Why you’ll love working here: 

Benefits Cafeteria — annual budget you allocate to:

Sports • Medical • Mental health • Home office • Languages.

Work-life & support

• Paid maternity/paternity leave + monthly childcare allowance.
• 20+ vacation days, unlimited sick leave, emergency time off.
• Remote-first + tech support + coworking compensation.
• Team events (online/offline/offsite).
• Learning culture with internal courses + growth programs.

Our culture & core values:

GR8 Tech culture is how we win — through trust, ownership, and a growth mindset. We move fast, stay curious, and keep it real, with open feedback, room to experiment, and a team that’s got your back.

FUELLED BY TRUST: we’re open, honest, and have each other’s backs.

OWN YOUR GAME: we take initiative and own what we do.

ACCELER8: we move fast, focus smart, and keep it simple.

CHALLENGE ACCEPTED: we grow through challenges and stay curious.

BULLETPROOF: we’re resilient, ready, and always have a plan.

Client

Our client is a leading AI‑powered workforce transformation and talent management platform.

Position overview

We are seeking a Senior Data Engineer / Team Lead to join a rapidly growing data organization powering an AI-driven HR technology platform used by enterprise customers worldwide.

This is a hands-on senior engineering role focused on building, operating, and evolving a modern data platform leveraging Google BigQuery and Kubernetes-based services. The position blends data engineering, analytics enablement, and platform ownership to deliver reliable, scalable, and high-quality data solutions used across internal teams and customer-facing analytics products.

The successful candidate will collaborate closely with product, engineering, and analytics teams to build robust data pipelines, enable reporting capabilities, and contribute to technical best practices and platform evolution. During an initial transition period, the role may also include technical leadership responsibilities until a dedicated Engineering Manager joins.

Responsibilities

• Design, build, and maintain scalable data pipelines using modern ELT practices.
• Develop and optimize data models within BigQuery and ensure performance, reliability, and cost efficiency.
• Operate and enhance Kubernetes‑based data services as part of the data platform.
• Build clean, reusable datasets to support analytics and reporting needs.
• Support the development of customer‑facing dashboards and analytics features.
• Define and maintain core business metrics and the associated data transformations.
• Enable self‑service data access for internal teams across the organization.
• Implement monitoring, alerting, and observability for all data workflows and pipelines.
• Ensure data correctness, consistency, and overall operational stability.
• Troubleshoot production data issues and drive improvements to system resilience.
• Provide technical guidance and mentorship to engineers during the transition period.
• Participate in design discussions, architecture decisions, and engineering best practices.
• Collaborate closely with product, analytics, and engineering teams to deliver scalable solutions.
• Translate business requirements into well‑designed technical implementations.
• Contribute to continuous improvements in development workflows and team processes.

Requirements

• Strong experience with SQL and data modeling.
• Hands-on experience with Google BigQuery or comparable cloud data warehouses.
• Proven ability to build and operate data pipelines in production environments.
• Programming proficiency in Python, Java, or Node.js.
• Experience working with containerized environments, including Docker and Kubernetes.
• Solid understanding of modern ELT workflows and analytics engineering practices.
• Experience using dbt or similar data transformation frameworks.
• Background supporting customer-facing analytics products.
• Exposure to AI and machine learning data workflows.
• Experience implementing monitoring and alerting for production systems.
• Familiarity with Infrastructure as Code concepts, such as Terraform.
• Strong systems design capabilities and problem‑solving skills.
• Experience working in cloud-native engineering environments.
• Ability to clearly communicate technical concepts to cross-functional stakeholders.
• Comfortable operating in fast-paced product-driven environments.
• Strong ownership mindset with the ability to work autonomously.

We are looking for a Data / Backend Engineer to architect and scale the core data infrastructure behind our healthcare marketing platform. In this role, you will design high-throughput data systems that process millions of behavioral events, power real-time attribution and user scoring, and enable precise targeting of healthcare professionals across 20+ channels.

You will work at the intersection of data engineering, backend systems, and marketing infrastructure, building scalable pipelines, tracking systems, and APIs that support analytics, segmentation, and campaign activation. The role also involves experimenting with AI-powered automation and agent-based workflows to improve internal operations and product capabilities.

This is a high-ownership position where you will shape architecture decisions, build critical platform components from the ground up, and help evolve our data platform as the company scales.

Responsibilities

- Architect and own data-heavy backend systems powering real-time attribution, user modeling, and scoring

- Build and evolve client-side tracking pixels (like FB pixel / Amplitude snippet / Heap autocapture) from scratch

- Set up and manage scalable ETL workflows: cleaning, merging, enriching, splitting, transforming across millions of behavioral events
Lead the build of CDP / CDXP-style data layers to support segmentation, scoring, and activation across channels

- Connect and compose systems using modern low-code / no-code tools (n8n) to accelerate ops

- Implement and maintain high-availability APIs for analytics, scoring, and campaign delivery

- Drive experimentation around AI-powered agents and automation tools that can boost internal workflows

Requirements

- System Design & Data Architecture:
Designs scalable, event-driven data platforms with strong decoupling, fault tolerance, and horizontal scalability. Builds real-time and batch pipelines using lakehouse architectures and streaming systems (Kafka / PubSub).

- Distributed Data Processing (Spark / BigQuery / Iceberg):
Expert in large-scale data processing, query optimization, and cost-efficient analytics. Deep understanding of Spark execution, partitioning, and modern table formats (Iceberg / Delta).

- Cloud & Infrastructure (GCP / Kubernetes):
Builds resilient cloud-native data platforms on GCP and Kubernetes using IaC, autoscaling, and secure access (IAM, Workload Identity).

- Python Engineering:
Develops high-performance Python services for data and ML workloads with focus on concurrency, clean architecture, and production-grade quality.

- Databases & Performance (PostgreSQL / OLTP):
Optimizes high-throughput OLTP systems through indexing, partitioning, and query analysis (EXPLAIN ANALYZE, MVCC).

- Reliability & Observability (SRE):
Implements resilient data systems with idempotency, retries, observability, SLOs, and incident management.

- AI / LLM Integration:
Integrates LLMs into production pipelines with structured outputs, caching, batching, prompt versioning, and evaluation.

- Workflow Orchestration (Airflow / Dagster):
Designs scalable DAG-based workflows with dependency management, retries, and reproducible backfills.

- CI/CD & DevOps for Data:
Implements safe deployments for data systems including schema migrations, canary releases, and data contracts.

- Ownership & Engineering Maturity:
Owns end-to-end production systems and architecture decisions while balancing delivery speed, quality, and technical debt.

Nice-to-have: 

- Experience in MarTech / AdTech platforms (e.g., DSPs, attribution systems, DMP/CDP tools)

- Deep knowledge of data matching/fingerprinting techniques (identity graphs, IP + UA resolution, hashed PII workflows)

- Strong prompt engineering skills — not just ChatGPT 101, but chaining, system prompting, tooling integration

What We Offer
- Fully remote with flexible hours (aligned with EU timezones for syncs).
- Influence on quality strategy across the entire engineering organization.
- A cross-team role with visibility into every part of the product.
- AI-first tooling.
- Claude Code licenses and cutting-edge AI development workflows. 
- A team with no bureaucracy, decisions are made fast.

We are looking for a Senior Data Engineer to join the Identity team at Equals5. This is not a standard ETL role. We are building a dynamic data ecosystem where AI is deeply integrated—both as a productivity multiplier and as a core component of our data processing logic for identity data enrichment and data scoring.

You will own the infrastructure that handles over 10,000 executions per minute, ensuring stability, scalability, and data integrity. You will work with a modern stack on Google Cloud Platform, utilizing Cloud Functions and Kubernetes.

We are looking for an engineer who improves infrastructure, automates everything, and is eager to implement LLM-based logic directly into high-load data flows.
 

Responsibilities

• AI-Driven Data Scoring: Design and implement pipelines that utilize LLMs to analyze and score identity data in real-time. You will integrate AI models directly into the decision-making loop, balancing accuracy with latency and cost.
• Own the Data Architecture: Architect scalable data solutions using GCP and Python. You will manage data storage and retrieval using BigQuery and Apache Iceberg to support querying of TBs of data.
• Heavy Data Processing: Utilize Apache Spark for data transformations and batch processing when lightweight cloud functions are not enough.
• Manage High-Load Orchestration: Maintain and optimize our system instances. It involves complex dataflows, custom Python nodes, and performance tuning for 10k+ execs/minute.
• Release Lifecycle (CI/CD): Take ownership of the deployment process, ensuring that updates to pipelines and infrastructure are released safely with proper testing and rollback strategies.
• Database Optimization: Manage PostgreSQL performance under heavy load, optimizing complex queries and indexing strategies.
• Active AI Usage: Use Claude Code and other AI engineering tools to accelerate your own development, refactoring, and testing processes.
• Incident Resolution: Proactively monitor the system. When alerts fire, you investigate the root cause—whether it’s a database lock or an LLM hallucination—and fix it permanently.
   

Requirements

• 4-5+ years of experience in Data Engineering or Backend Engineering with a strong data focus.
• Production AI Integration: Experience integrating LLMs (OpenAI, Anthropic, Gemini) into production applications via API. You understand latency, token limits, and how to structure data for AI scoring.
• Expertise in GCP: Understanding of Google Cloud Platform (Cloud Functions, IAM, Networking).
• Strong Python: You write clean, efficient, and testable code. You are comfortable building custom logic where standard tools fall short.
• Big Data Stack: Experience with BigQuery, Apache Spark, and modern table formats like Apache Iceberg.
• Kubernetes (K8s): Experience deploying and scaling services in containerized environments.
• Workflow Automation: Understanding of workflow orchestration tools at a deep technical level. N8N is a big part of our domain, so familiarity with it is highly valuable.
• PostgreSQL Mastery: Proven ability to handle heavy write/read loads and optimize schemas.
• English: B2+ (Upper-Intermediate) or higher.
   

Culture & Mindset

• Self-improvement: You are a fast learner. You don't fear AI replacing you; you master it to replace your manual tasks.
• Ownership: You treat the Identity domain as your own business. If a scoring model drifts or a pipeline slows down, you notice it and fix it without being asked.
• Internal Locus of Control: You take responsibility for outcomes. If an external API fails, you build a fallback mechanism instead of just blaming the provider.
• Get It Done: You prioritize shipping value. You know when to use a simple script and when to build a complex architecture.
• Openness: You share knowledge freely. If you find a better way to prompt the AI for scoring, you share it with the team.
   

What We Offer

• Fully remote with flexible hours (aligned with EU timezones for syncs).
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech for both daily coding and product features.
• High-Impact Role: You will directly influence how we identify and score users, impacting the core business logic.
• Cross-functional visibility: Work closely with Product and Tech Leads to shape the future of Identity.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.

Build the data backbone for scalable analytics

Softsich is a young and ambitious international product tech company that develops scalable B2B digital platforms. We’re on the lookout for an experienced Data Engineer who’s ready to grow with us and shape high-load, data-driven solutions used by international partners.

In this role, you will expand and maintain our AWS-based data warehouse, design analytical data models, and build reliable data pipelines that power reporting and business intelligence. If you enjoy working with modern data infrastructure, optimizing pipelines, and collaborating closely with analysts and product teams — this role may be a great match.

Your key responsibilities will include:

– Extend and maintain the existing AWS-based data warehouse by expanding the dbt infrastructure and developing new transformation models using SQL and dbt.
– Design and optimize analytical data models in Amazon Redshift to support reporting and business intelligence use cases.
– Develop and maintain data pipelines orchestrated in Amazon MWAA (Airflow) using Python-based DAGs.
– Migrate existing data pipelines from AWS Glue to MWAA to improve orchestration, maintainability, and scalability.
– Build data ingestion and transformation workflows that process data from multiple sources such as Kafka, MongoDB, and PostgreSQL.
– Implement data validation and verification scripts using Python, pandas, and numpy to ensure data quality and reliability.
– Collaborate with analysts and product owners to deliver well-structured datasets and ensure data integrity, performance, and accessibility.

It’s a match if you have:

– 3+ years of experience in data engineering or related roles.
– Strong understanding of data warehousing concepts, ETL/ELT processes, and data transformation techniques (MWAA preferred).
– Hands-on experience with data ingestion and processing using Kafka.
– Proficiency in SQL and experience with relational and NoSQL databases such as PostgreSQL and MongoDB.
– Experience with Python programming for data processing, automation, and pipeline development.
– Ability to work independently, take ownership of data systems, and collaborate effectively with analysts and product owners.
– Excellent communication and collaboration skills.

What we offer:

– Flexible schedule and remote format or offices in Warsaw/Kyiv — you choose.
– 24 paid vacation days, sick leaves, and health insurance (UA-based, other locations in progress).
– A supportive, friendly team where knowledge-sharing is part of the culture.
– Coverage for professional events and learning.
– Birthday greetings, team buildings, and warm human connection beyond work.
– Zero joules of energy to the aggressor state, its affiliated businesses, or partners.

Send over your CV now — we’d love to get to know you better!

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

Requirements

MUST HAVE:

• AWS Platform: Working experience with AWS services – in particular serverless architectures (S3, RDS, Lambda, IAM, API Gateway, etc…) supporting API development in a microservices architecture

• Programming Languages: Python (strong programming skills), Go or other languages

• Data Formats: Experience with JSON, XML and other relevant data formats

• CI/CD Tools: experience setting up and managing CI/CD pipelines using GitLab CI, Jenkins, or similar tools

• Scripting and automation: experience in scripting language such as Python, PowerShell, etc…

• Monitoring and Logging: Familiarity with monitoring & logging tools like CloudWatch, ELK, Dynatrace, Prometheus, etc…

• Source Code Management: Expertise with git commands and associated VCS (Gitlab, Github, Gitea or similar)

• Terraform

NICE TO HAVE

• Strongly Preferred: Infrastructure as Code: Experience with Terraform and CloudFormation – Proven ability to write and manage Infrastructure as Code (IaC)
• Documentation: Experience with markdown and in particular Antora for creating technical documentation
• Experience working with Healthcare Data, including HL7v2, FHIR and DICOM
• FHIR and/or HL7 Certifications
• Building software classified as Software as a Medical Device (SaMD)
• Understanding of EHR technologies such as EPIC, Cerner, etc…
• Experience implementation enterprise grade cyber security & privacy by design into software products
• Experience working in Digital Health software
• Experience developing global applications
• Strong understanding of SDLC – Waterfall & Agile methodologies
• Software estimation
• Experience leading software development teams onshore and offshore

Job responsibilities

• Develops, documents, and configures systems specifications that conform to defined architecture standards, address business requirements, and processes in the cloud development & engineering.
• Involved in planning of system and development deployment as well as responsible for meeting compliance and security standards.
• API development using AWS services
• Experience with Infrastructure as Code (IaC)
• Actively identifies system functionality or performance deficiencies, executes changes to existing systems, and tests functionality of the system to correct deficiencies and maintain more effective data handling, data integrity, conversion, input/output requirements, and storage.
• May document testing and maintenance of system updates, modifications, and configurations.
• May act as a liaison with key technology vendor technologists or other business functions.
• Function Specific: Strategically design technology solutions that meets the needs and goals of the company and its customers/users.
• Leverages platform process expertise to assess if existing standard platform functionality will solve a business problem or customization solution would be required.
• Test the quality of a product and its ability to perform a task or solve a problems.
• Perform basic maintenance and performance optimization procedures in each of the primary operating systems.
• Ability to document detailed technical system specifications based on business system requirements
• Ensures system implementation compliance with global & local regulatory and security standards (i.e. HIPAA, SOCII, ISO27001, etc…)

About Us

Axia is a deal origination firm that connects investment banks and private equity firms with qualified deal flow. We're a bootstrapped team of 20 — lean, fast-moving, and growing.

The Role

You'll own our entire data sourcing process — finding, extracting, enriching, and delivering the data that powers our deal origination engine. You'll work heavily with Clay, APIs, web scraping, and third-party data providers to build reliable pipelines that feed our outreach and research teams.

What You'll Do

- Own the full data sourcing process — from identifying sources to delivering clean, enriched datasets to the team

- Build and maintain Clay workflows — design multi-step Clay tables that enrich, filter, and score leads at scale

- Integrate third-party APIs — connect data providers, enrichment tools, and internal systems into automated pipelines

- Build and maintain web scrapers — extract structured data from websites, directories, and public sources

- Ensure data quality — validate, deduplicate, and normalize data before it reaches outreach and research teams

- Evaluate new data sources — research and test new providers, tools, and methods to improve coverage and accuracy

- Document processes — maintain clear documentation so workflows are repeatable and not dependent on one person

What We're Looking For

Must-have:

- Strong experience with Clay (building complex tables, enrichment workflows, API integrations within Clay)

- Proficiency working with REST APIs — authenticating, paginating, transforming responses

- Web scraping experience — Python (BeautifulSoup, Scrapy, Playwright) or similar tools

- Comfortable cleaning and transforming messy data into structured, usable formats

- Professional English — clear written communication for async collaboration

- Some availability during US Eastern Time hours (full overlap not required)

Nice-to-have:

- Experience with data enrichment providers (Apollo, ZoomInfo, Clearbit, PeopleDataLabs, etc.)

- SQL and database experience (PostgreSQL, BigQuery, or similar)

- Familiarity with no-code/low-code automation tools (Make, Zapier, n8n)

- Background in B2B data, lead generation, or deal sourcing

- Experience with Python scripting beyond scraping (pandas, data pipelines)

Compensation

- Monthly payment based on experience

- Full-time contractor engagement

- Long-term role with growth potential as our data operations scale

Location

Remote — some overlap with US Eastern Time (EST) preferred, but full overlap not required.

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).

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

PwC is seeking an experienced Databricks Platform Engineer to accelerate the maturation of our Databricks platform as a core component of the firm’s Data Mesh and AI-first strategy. This role will help shape the architectural direction, governance model, and enterprise standards that underpin secure and scalable Databricks adoption.

Role Overview

The Databricks Platform Engineer  will be responsible for executing against this strategy by driving service optimization, implementing advanced platform capabilities, and partnering with Product and Engineering teams to enable enterprise-scale adoption across client and corporate use cases.

Key Responsibilities:

• Lead the rollout and optimization of Databricks services at the PwC account level.
• Implement advanced capabilities including Unity Catalog, AI/ML models, Delta Sharing, Automatic Identity Management (AIM/SCIM), and Budget Policies for cost governance and tagging.
• Collaborate with Databricks and PwC platform teams to enhance and enable secure data exchange.
• Support networking design and optimization across Databricks environments.
• Partner with Product and Engineering teams to refine user experience, service provisioning models, and upcoming Databricks capabilities.
• Coordinate cross-functional efforts to enable AI-driven workflows and advanced analytics capabilities within Databricks.

Required Qualifications:

• 5+ years of experience in data engineering, cloud data platforms, or platform architecture.
• 3+ years of hands-on experience with Databricks or comparable modern data platforms.
• Expertise in Unity Catalog, Delta Sharing, Compute (classic and serverless), Microsoft Entra ID (SCIM/AIM), and Azure networking.
• Strong understanding of data governance, access control models, and FinOps best practices.
• Excellent communication skills with the ability to translate complex technical solutions into business value.

Preferred Qualifications:

• Databricks Certified Professional or Azure Databricks Certification.
• Hands-on experience with Databricks, Microsoft Fabric / OneLake, or other enterprise data platforms.
• Prior consulting experience or enterprise-scale platform transformation experience.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

Location: Warsaw

The Project
You'll be joining a platform that's redefining how private capital markets operate — think PE firms, venture funds, and hedge funds using AI to make faster, smarter decisions on complex financial data.
This isn't a maintenance role. You'll be one of the key engineers shaping the data foundation of an AI-native PaaS/SaaS product from the ground up: designing schemas that LLMs can actually reason over, building pipelines that don't fall apart under real enterprise load, and untangling the legacy architecture that got the product to where it is today.
The problems are genuinely hard. The data is messy, the domain is complex, and the stakes are high — which is exactly what makes it interesting.

What You'll Be Working On
 

• Architect cloud-native data topologies and AI-friendly ontologies for structured and unstructured financial data
• Design and own scalable ETL/ELT pipelines using Prefect or Airflow
• Reverse-engineer and optimize existing data infrastructure

• Implement data governance, security standards, and CI/CD practices across the data layer

   

What We're Looking For

Must-have:

• 3+ years with Python (Pandas, ETL frameworks)
• 5+ years with complex SQL and RDBMS
• 5+ years of ETL orchestration (Airflow, Prefect)
• Hands-on experience with cloud DW: Redshift, Snowflake, or RDS
• Strong grasp of data modeling — OLAP, OLTP, Star/Snowflake schemas
• English B2+ — you'll communicate directly with the founding team

Nice to have: Docker, Kubernetes, PySpark, AWS Lambda, cloud certifications

Why This Role
 

• You'll have real architectural ownership, not just ticket execution
• The domain (private capital + AI) is genuinely niche and growing fast
• Direct access to founders — short feedback loops, no bureaucracy
• A team that takes engineering quality seriously and actually means it
   

Hiring Process Intro call → Technical Interview → Final with Founding Team

 

On behalf of our client, we are looking for a Solution Architect (Digital Commerce / SF Data Cloud) 

Requirements:

- Bachelor’s degree in Computer Science or related field

- 5+ years of client-facing experience in consulting / professional services

- Proven track record in designing and selling eCommerce solutions

- Strong experience with enterprise platforms (SFCC, SAP Hybris, Magento)

- Hands-on experience with SF Data Cloud (must-have)

- Experience leading projects end-to-end

- Strong business communication and stakeholder management skills

- Proactive, self-driven, and collaborative mindset

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

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.

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)

What We’re Looking For

• Strong foundation in cybersecurity
• Hands-on experience with at least one major cloud platform (AWS preferred; Azure or GCP also valid). Comfort navigating services, permissions models, and APIs/SDK concepts.
• Ability to translate security and customer needs into high-value product work (prioritization, impact vs effort, clear definitions of “done”).
• Good communication skills: you can explain security decisions and tradeoffs to both technical and non-technical stakeholders.
• Solid engineering literacy (you can read and review code, reason about reliability and edge cases). Deep coding expertise is not required.

Bonus Points For

• Experience with CSPM/CNAPP tools, security research, or building detection/analytics pipelines.
• Familiarity with cloud telemetry/log sources and correlating security signals.
• Comfort with Infrastructure as Code concepts (e.g., Terraform) and cloud-native environments.