Jobs Data Engineer

We are a global audience and location intelligence company that helps marketers connect the digital and physical world. We provide data-driven solutions to enhance marketing campaigns by leveraging location and audience data to reveal consumer behavior and enable more precise targeting and measurement. We work on high-end / high-performance / high-throughput systems for in-time analysis of data for autonomous driving and other big data applications e.g. for E-commerce.



Job Description

You have 4+ years of experience on similar position.

You have significant experience with Python. Familiarity with Java or Scala is a plus.

Hands-on experience building scalable solutions in AWS.

Proficiency in NoSQL and SQL databases and in high-throughput data-related architecture and technologies (e.g. Kafka, Spark, Hadoop, MongoDB, AWS Batch, AWS Glue, Athena, Airflow, dbt).

Excellent SQL and data transformation skills.

Excellent written and verbal communication skills with an ability to simplify complex technical information.

Experience guiding and mentoring junior team members in a collaborative environment.

Job Responsibilities

Work in a self-organised agile team with a high level of autonomy, and you will actively shape your team's culture.

Design, build, and standardise privacy-first big data architectures, large-scale data pipelines, and advanced analytics solutions in AWS.

Develop complex integrations with third-party partners, transferring terabytes of data.

Align with other Data experts on data (analytics) engineering best practices and standards, and introduce those standards and data engineering expertise to the team in order to enhance existing data pipelines and build new ones.

Successfully partner up with the Product team to constantly develop further and improve our platform features.

Tasks:

• Design and implementation of scalable hub-and-spoke data architectures
• Processing and analysis of large datasets in Google Cloud (BigQuery)
• Development and optimization of ETL/ELT pipelines (including CDC and SCD Type 1/2)
• Building near real-time data pipelines
• Implementation of infrastructure as code (Terraform)
• Ensuring data quality, performance, and scalability
• Collaboration with data and platform teams

Requirements:

• 3–5 years of experience as a Data Engineer or in a similar role
• Strong expertise in:
• Google Cloud (BigQuery)
• SQL and Dataform
• ETL/ELT processes (CDC, SCD Type 1/2)
• Experience with:
• Terraform (Infrastructure as Code)
• Streaming technologies (Pub/Sub, Dataflow, Apache Beam)
• Python and ideally Java
• Experience handling large datasets and cloud-based architectures
• Structured and independent working style

 Project details:

• Start: April 2026
• Duration: 6 months
• Workload: Full-time
• Location: 100% remote

We are looking for a Senior Data Engineer who can design, implement, and evolve scalable data systems in AWS.

Core Responsibilities
 

• Design and implement batch and streaming data pipelines using Apache Spark.
• Build and evolve a scalable AWS-based data lake architecture.
• Develop and maintain real-time data processing systems (event-driven pipelines).
• Own performance tuning and cost optimization of Spark workloads.
• Define best practices for data modeling, partitioning, and schema evolution.
• Implement monitoring, observability, and data quality controls.
• Contribute to infrastructure automation and CI/CD for data workflows.
• Participate in architectural decisions and mentor other engineers.

Required Qualifications
 

• 5+ years of experience in Data Engineering.
• Strong hands-on experience with Apache Spark (including Structured Streaming).
• Experience building both batch and streaming pipelines in production environments.
• Proven experience designing AWS-based data lake architectures: S3, EMR, Glue, Athena.
• Experience with event streaming platforms such as Apache Kafka or Amazon Kinesis.
• Experience implementing lakehouse formats such as Delta Lake.
• Strong understanding of partitioning strategies and schema evolution.
• Experience using SparkUI and AWS CloudWatch for profiling and optimization.
• Strong understanding of Spark performance tuning (shuffle, skew, memory, partitioning).
• Proven track record of cost optimization in AWS environments.
• Experience with Docker and CI/CD pipelines.
• Experience with Infrastructure as Code: Terraform, AWS CDK.
• Familiarity with monitoring and observability practices.
• Experience in the Financial domain.
• Experience running Spark workloads on Kubernetes.
• Experience implementing data quality frameworks or metadata/lineage systems.

About the client:

Our customer is the European online car market with over 30 million monthly users, with a market presence in 18 countries. As a Senior Data Engineer (with Data Analyst skills), you will play a pivotal role in shaping the future of online car markets and enhancing the user experience for millions of car buyers and sellers.

About the Role

As a Senior Data Engineer (with Data Analyst skills), your primary task will be to extract actionable insights from our data and advise the organization on them. To this end, you will perform analyses, convince stakeholders with your presentations, or make your results structurally visible via a dashboard. You will also liaise with product managers and marketing specialists to bring the opportunities you see in the data to fruition on our platforms, or to ensure that their ideas are correctly implemented. To ensure this, you will collaborate with the lead data and client’s data teams to implement tracking, contribute ideas on how the A/B test should be conducted, and analyze the effects of the adjustments. As part of your role, you’ll help transition the existing tech stack to the sophisticated data platform of the client.

Responsibilities:

• Migrating dashboards and underpinning analytics models from (Snowflake, dbt, Qlik) to (AWS, python) data platform
• Measuring the effectiveness of a new feature on the platform
• Analyzing and advising on the customer journey (of B2B and B2C customers)
• Analyzing the effectiveness of website personalization
• Maintaining the tag management system and Snowplow data models in DBT/SQL

Requirements: 

• You have 4+ years of relevant work experience as a Data Analytics Engineer
• You are analytical, curious, and detail-oriented
• You get energy from diverse work and solving complex data questions
• You have extensive knowledge of SQL or other languages. Preferably experience with GTM, A/B testing, and dashboarding
• Strong communication skills - you can explain insights and analytical solutions to technical and non-technical stakeholders
• High motivation, proactiveness, and a genuine enthusiasm for data and product analytics

• English level - at least Upper-Intermediate, both spoken and written  

   

The complete set of technologies the clients are currently using includes:

DBT, Snowflake SQL, Big data, AWS, AWS Quick Sight, Python, Docker, GA4, Salesforce, and Qlik. If you are excited to work with large amounts of data in a robust data stack, then this is the right place!

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently looking for a Business Development Executive to join one of our clients' team. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.

We are looking for a skilled Senior Data Engineer. This role, you will be responsible for building scalable data pipelines, working with large datasets, and optimizing data workflows in a cloud-based environment. You will collaborate closely with data and engineering teams to ensure efficient and reliable data processing.

Key Responsibilities

• Design, build, and maintain robust data pipelines (ETL/ELT)
• Work with Databricks for large-scale data processing using Spark and Delta Lake
• Optimize data workflows, performance, and data storage solutions
• Collaborate with cross-functional teams including data analysts, engineers, and stakeholders
• Ensure data quality, reliability, and scalability across systems
• Contribute to continuous improvement of data architecture and processes

Job requirements

1. Strong experience with Databricks (Spark / Delta Lake)
2. Proficiency in Python for data processing
3. Strong knowledge of SQL
4. Hands-on experience with ETL/ELT pipeline development
5. Experience with at least one cloud platform (AWS, Azure, or GCP)
6. Familiarity with Git and basic CI/CD practices

Nice to Have

• Experience with dbt
• Knowledge of streaming technologies (e.g., Kafka or similar)
• Experience with Terraform or Infrastructure as Code (IaC)

N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact.

 

This role is ideal for someone at the beginning of their data engineering career who wants to grow in a supportive environment. We value curiosity, a learning mindset, and the ability to ask good questions. If you’re motivated to develop your skills and become a strong Data Engineer over time, we’d be happy to help you grow with us 🚀

Responsibilities

• Support the implementation of business logic in the Data Warehouse under the guidance of senior engineers
• Assist in translating business requirements into basic data models and transformations
• Help develop, maintain, and monitor ETL pipelines using Azure Data Factory
• Participate in data loading, validation, and basic query performance optimization
• Work closely with senior team members and customer stakeholders to understand requirements and data flows
• Contribute to documentation and follow best practices in data engineering and development
• Gradually propose improvements and ideas as experience grows
  
   

Requirements

• Up to 1,5 years of experience in Data Engineering
• Basic hands-on experience with SQL and strong willingness to work with it as a core skill
• Familiarity with Microsoft Azure or strong motivation to learn Azure-based data solutions
• Understanding of relational databases and fundamentals of data modeling
• Ability to write clear and maintainable SQL queries
• Basic experience with version control systems (e.g. Git)
• Interest in data warehousing and analytical systems
• Familiarity with Agile ways of working (through coursework, internships, or first commercial experience)
• Strong analytical thinking and eagerness to learn from more experienced colleagues
  
   

Nice to Have

• Exposure to Azure Data Factory, dbt, or similar ETL tools
• Basic knowledge of Databricks
• Understanding of Supply Chain & Logistics concepts
• Any experience working with SAP data (MM or related modules)
   

    We are looking for an experienced Head of Analytics / Analytics Manager to lead the development and maintenance of company-wide reporting, manage core data sources, and drive the implementation of modern analytics and AI-enabled solutions. 
    This role combines hands-on expertise in Power BI, SQL, and Python with ownership of analytics processes, data quality, and a small analytics team. You will play a key role in ensuring reliable management reporting, supporting business growth, and evolving our analytics ecosystem.


Key Responsibilities

• Design, build, and maintain Power BI dashboards and reports for company management and business stakeholders ;
• Own and manage global data sources, including:
 - HRM system ;
 - Time tracking system ;
 - Agent schedules and workforce data ;

• Fully build and support reporting and data logic for the company’s main project, ensuring data accuracy and consistency ;

• Implement reporting for new projects, including: 
- Connecting to new data sources o Integrating data via APIs ;
- Creating new dashboards and data models; 

• Develop and improve data models and DAX calculations in Power BI ;

• Write and optimize SQL queries and data transformations; 

• Participate in the development of Microsoft Fabric capabilities within existing processes; 

• Coordinate implementation of ML / forecasting solutions together with external vendors; 

• Lead and manage a small team: Reporting & Data Analyst and Operational Analyst;
• Define priorities, distribute tasks, and review results;

• Ensure documentation, stability, and reliability of reporting solutions;

• Collect, process, and analyze Customer Experience (CX) data (CSAT, NPS, CES, QA scores, customer feedback, complaints, etc.)
• Build CX dashboards and analytical views to monitor service quality and customer satisfaction
  
  Required Qualifications
   
• Higher education in IT, Computer Science, Mathematics, Finance, or related field;
• 3+ years of hands-on experience with Power BI;
• Strong and practical knowledge of DAX;
• 3+ years of experience with SQL and building complex queries;
• 1+ year of experience with Python (for data processing / automation / ETL tasks);
• Experience connecting to external systems via APIs;
• Solid understanding of data modeling and BI best practices;
• Experience working with large datasets;
• English level: B1 or higher;

Nice to Have
 

• Experience with Microsoft Fabric (Dataflows Gen2, Lakehouse/Warehouse, Notebooks, Pipelines);
• Exposure to forecasting or machine learning concepts;
• Experience in BPO / Contact Center / Operations analytics;

What We Offer

• Opportunity to build and shape the analytics function
• Direct impact on management decision-making
• Participation in AI-driven analytics transformation
• Professional growth in a fast-scaling company

About ListKit

ListKit is a B2B lead generation platform processing 825M+ person records, serving thousands of customers across DFY (done-for-you) and PLG (self-serve) segments. Our data enrichment pipeline runs on Google Cloud (Cloud Run, PubSub, Cloud Tasks, Firestore) with TypeScript/Node.js, backed by SingleStore for high-performance JOINs against our 825M+ record dataset and SQL Server for transactional order data.

We are an AI-first engineering team. Every engineer uses Claude (Anthropic) as a core development tool for architecture decisions, code review, debugging, estimation, and daily workflows. If you haven't worked with AI coding tools yet, that's fine, but you need to be excited about making it your primary way of working.

The Role

You will own the cloud-native data enrichment platform that powers ListKit's core product: turning customer search criteria into verified, enriched lead lists.

The enrichment service (TypeScript/Node.js on GCP) orchestrates the full pipeline: receiving order requests, querying 825M+ records via SingleStore stored procedures, routing records through email finder APIs (Enrow, Prospeo, LeadMagic) and email verifiers (MillionVerifier, TryKitt), tracking job lifecycle via Firestore counters, processing billing/refunds, and delivering final exports to GCS.

The integration challenge: This service must work in lockstep with our .NET backend, which manages the customer-facing order lifecycle in SQL Server. Today, these are two disconnected state machines. Your first major project is building the completion bridge so the enrichment platform's results flow back to the .NET order processing pipeline. You don't need to be a .NET developer; we have a strong .NET team. But you need to understand the integration surface and design clean APIs between the two systems.

What You Will Do

First 30 days

• Take ownership of the listkit-enrichment codebase (TypeScript/Node.js, Cloud Run)
• Understand the full enrichment flow: PubSub dispatch, Cloud Tasks per-row processing, provider waterfall, verification chains, Firestore lifecycle counters, SingleStore JOINs, billing/refund integration
• Build the completion callback: when GCP enrichment finishes, write results back to SQL Server's OrderProcessing table so the .NET pipeline detects completion
• Fix the data-retrieval PubSub subscriber gap

First 90 days

• Own the enrichment platform end-to-end: reliability, performance, monitoring, alerting
• Improve provider waterfall logic: smarter failover between Enrow, Prospeo, LeadMagic, and the SingleStore JOIN path
• Build observability: structured logging, Cloud Monitoring dashboards, SLA tracking per provider
• Reduce enrichment latency for large orders (1000+ records)
• Work with the .NET team to design the target architecture where GCP enrichment fully replaces the Windows Services

Ongoing

• Adding external email finding/verification API providers to Cloud Run/Cloud Tasks
• Optimize SingleStore stored procedures (sp_enrich_csv) for the 825M+ record dataset
• Scale the enrichment platform for higher throughput as order volume grows
• Build and maintain the external enrichment API (API key auth, rate limiting, usage tracking)
• Contribute to infrastructure-as-code (Terraform for GCP resources)

Required Skills

TypeScript/Node.js (3+ years)

• Express.js, async/await, Promises, streaming
• Building and consuming HTTP APIs at scale
• Error handling in distributed async workflows (retries, idempotency, dead-letter queues)

Google Cloud Platform (2+ years, or equivalent AWS/Azure)

• Cloud Run (containerized services, autoscaling, concurrency)
• PubSub (message queues, subscriptions, delivery guarantees)
• Cloud Tasks (HTTP task dispatch, rate limiting, retry policies)
• Firestore (document database, transactions, atomic counters)
• GCS (object storage, signed URLs, streaming reads)
• Terraform (infrastructure-as-code)

Database experience

• SQL: complex JOINs, stored procedures, query optimization against 100M+ row tables
• SingleStore, MySQL, or PostgreSQL (enrichment service uses SingleStore)
• Basic SQL Server knowledge for the integration surface

Distributed systems thinking

• State tracked across multiple stores (Firestore + SingleStore + SQL Server)
• Eventual consistency, idempotency guards, distributed locking
• Job lifecycle management: queued, processing, completed, failed
• Rate limiting against third-party APIs with different throttle characteristics

AI-first development mindset

• Experience with AI coding assistants (Claude, GitHub Copilot, Cursor, or similar)
• Willingness to use Claude as your primary tool for code review, debugging, architecture, and estimation
• We estimate all engineering work assuming AI-assisted development. Mechanical work compresses dramatically. You estimate only irreducible human work.

Nice to Have

• Experience integrating with third-party enrichment/data APIs (email finders, verifiers, data providers)
• Experience building multi-tenant SaaS APIs with API key authentication and per-plan rate limiting
• Stripe billing integration (credits, refunds, usage-based pricing)
• Understanding of .NET/C# (reading code, understanding integration points)
• Event-driven architectures and CQRS patterns
• Familiarity with Linear for project management

How We Work

• AI-first: Claude is embedded in everything we do. Code review, spec writing, debugging, Linear issue management. We track AI adoption scores and expect engineers to reach Vanguard tier.
• Async by default: Team spans Lisbon (WET/WEST), Ukraine (EET) and US. Written communication via Slack, Linear, and documented decisions.
• Ship fast, fix fast: Continuous deployment for hotfixes, scheduled release trains for features. Production incidents get addressed immediately.
• Ownership mentality: You own your systems end-to-end. If the enrichment platform breaks, you fix it.

Tools & Stack

Your primary stack

• TypeScript (Node.js 20+) on Google Cloud Run
• Google Cloud: PubSub, Cloud Tasks, Firestore, GCS, Secret Manager, Cloud Build
• SingleStore (825M+ row dataset, stored procedures, columnar JOINs)
• Terraform (infrastructure-as-code)
• Third-party APIs: Enrow, Prospeo, LeadMagic, MillionVerifier, TryKitt, AtData

Integration surface

• SQL Server (read/write to OrderProcessing table for the .NET bridge)
• .NET backend (you design the API contract; the .NET team implements their side)

Shared tooling

• Claude (Opus/Sonnet via claude.ai, Claude Code CLI, MCP connectors)
• Linear (project management with Claude-integrated workflows)
• Slack, Google Meet, Granola (meeting notes)
• GitHub Actions (CI/CD), Stripe (billing), Intercom (support), HubSpot (CRM)

How to Apply

Send your CV and a short note (3-4 sentences) answering one of:

1. "Describe a Cloud Run or serverless service you built that processes jobs asynchronously via PubSub/SQS/EventBridge. How did you handle job lifecycle, retries, and completion detection?"

2. "Tell us about a time you had to integrate two systems that tracked state in different databases. How did you design the bridge?"

We will prioritize candidates who can start within 2-3 weeks.

We are looking for a talented and experienced software engineer for the project which is related to the development of the brand-new databricks platform for unification of data streams from different streaming services for the global media and entertainment company that encompasses a diverse portfolio of television networks, film studios, theme parks and digital platforms.
The engineer will have the opportunity to be part of a strong R&D group that creates a cutting-edge solution designed to streamline and optimize business operations, provide seamless order processing, inventory management and real-time tracking by ensuring efficient and accurate order fulfillment.

Job Description

4+ years in data engineering
2+ years with Databricks
Strong Python and SQL
Hands-on experience with PySpark
Experience building production data pipelines with Delta Lake
Experience with orchestration tools such as Airflow, Databricks Workflows, or similar
Experience with APIs, ingestion jobs, and data transformation frameworks
Experience with testing, observability, and pipeline reliability
 

Job Responsibilities

Build and maintain scalable Databricks pipelines for customer and audience data
Integrate internal product, CRM, and third-party marketing datasets
Design data models for segmentation, activation, and reporting
Ensure data quality, privacy compliance, and operational reliability
Work with analysts, marketers, and platform teams on customer 360 use cases
Optimize Spark jobs for performance and cost

The company helps hotel chains like Hilton and Marriott transform front-desk staff into revenue generators through upselling training and analytics. Their IN-Gauge SaaS platform empowers frontline teams across 2,000+ properties in over 100 countries.

- Implement scaling of the case detection process (scanner)
- Split API into multiple API services
- Emulate pubsub/cloud run locally
- Implement scaling of the case detection process (scanner)
- Split API into multiple API services
- Emulate pubsub/cloud run locally
- Extract & process data using PySpark + S3 (Kafka/Kinesis — bonus)
- Write & optimize SQL on PostgreSQL/Redshift; use DynamoDB as data source/sink
- Run and debug ETL jobs on Glue or EMR; monitor via console/Spark UI

Requirements:

• Data engineering - 5 years
• AWS - 3 years (1 year latest project)
• Spark/PySpark - 2 years (1 year latest project)

Ask candidates the following questions:

• How do you use AI tools in your work as a data engineer?
• Can you share specific examples where it improved your efficiency or quality of work?
• What’s your experience with ELT & ETL? 

Important: ability to work in high load environments, we're looking for autonomous and proactive candidates

Description

As the Data Architect, you will be the senior technical visionary for the Data Platform. You will be responsible for the high-level design of the entire solution, ensuring it is scalable, secure, and aligned with the company’s long-term strategic goals. Your decisions will form the technical foundation upon which the entire platform is built, from initial batch processing to future real-time streaming capabilities.

Requirements

– Cloud Architecture: Extensive experience designing and implementing large-scale data platforms on Microsoft Azure.
– Expert Technical Knowledge: Deep, expert-level understanding of the Azure data stack, including ADF, Databricks, ADLS, Synapse, and Purview.
– Data Concepts: Mastery of data warehousing, data modeling (star schemas), data lakes, and both batch and streaming architectural patterns.
– Strategic Thinking: Ability to align technical solutions with long-term business strategy.

Nice-to-Have Skills:

– Hands-on Coding Ability: Proficiency in Python/PySpark, allowing for the creation of architectural proofs-of-concept.
– DevOps & IaC Acumen: Deep understanding of CI/CD for data platforms and experience with Infrastructure as Code (Bicep/Terraform)/Experience with AzureDevOps for BigData services
– Azure Cost Management: Experience with FinOps and optimizing the cost of Azure data services.

Job responsibilities

– End-to-End Architecture Design: Design and document the complete, end-to-end data architecture, encompassing data ingestion, processing, storage, and analytics serving layers.
– Technology Selection & Strategy: Make strategic decisions on the use of Azure services (ADF, Databricks, Synapse, Event Hubs) to meet both immediate MVP needs and future scalability requirements.
– Define Standards & Best Practices: Establish data modeling standards, development best practices, and governance policies for the engineering team to follow.
– Technical Leadership: Provide expert technical guidance and mentorship to the data engineers and BI developers, helping them solve the most complex technical challenges.
– Stakeholder Communication: Clearly articulate the architectural vision, benefits, and trade-offs to technical teams, project managers, and senior business leaders.

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

Description

The GlobalLogic technology team is focused on next-generation health capabilities that align with the client’s mission and vision to deliver Insight-Driven Care. This role operates within the Health Applications & Interoperability subgroup of our broader team, with a focus on patient engagement, care coordination, AI, healthcare analytics, and interoperability. These advanced technologies enhance our product portfolio with new services while improving clinical and patient

experiences.

Requirements

An AWS Data Engineer designs, develops, and maintains scalable data solutions using AWS cloud services.

Key Responsibilities:
    • Design, build, and manage ETL (Extract, Transform, Load) pipelines using AWS services (e.g., Glue, Lambda, EMR, Redshift, S3).
    • Develop and maintain data architecture (data lakes, warehouses, databases) on AWS.
    • Implement data quality and governance solutions.
    • Automate data workflows and monitor pipeline health.
    • Ensure data security and compliance with company policies.
Required Skills:
    • Proficiency with AWS cloud services, especially data-related offerings (S3, Glue, Redshift, Athena, EMR, Kinesis, Lambda).
    • Strong SQL and Python skills.
    • Experience with ETL tools and frameworks.
    • Familiarity with data modelling and warehousing concepts.
    • Knowledge of data security, access management, and best practices in AWS.
Preferred Qualifications:
    • AWS certifications (e.g., AWS Certified Data Analytics – Speciality, AWS Certified Solutions Architect).
    • Background in software engineering or data science.

• Hands-on experience with Oracle Database and log-based Change Data Capture (CDC) replication using AWS Database Migration Service (DMS) for near real-time data ingestion.

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 in a scalable, microservices-based architecture

– 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 meet 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 if a customisation solution would be required.

– Test the quality of a product and its ability to perform a task or solve a problem.

– Perform basic maintenance and performance optimisation 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.)

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About Us:

Atto Trading, a dynamic quantitative trading firm founded in 2010 and leading in global high-frequency strategies, is looking for a Data Engineer to join our team.

We are expanding an international, diverse team with experts in trading, statistics, engineering, and technology. Our disciplined approach, combined with rapid market feedback, allows us to quickly turn ideas into profit. Our environment of learning and collaboration allows us to solve some of the world’s hardest problems, together. As a small firm, we remain nimble and hold ourselves to the highest standards of integrity, ingenuity, and effort. 

Role Highlights:
We are seeking an experienced Senior Data Engineer to design, build, and maintain our comprehensive Data Lake for a fast-growing number of research and production datasets. This role combines hardware and platform infrastructure expertise with data engineering excellence to support our rapidly growing data assets (~200TB current, scaling ~100TB/year). 
 

Responsibilities:

• Architect and manage high-performance, scalable on-premise data storage systems optimized for large-scale data access and analytics workloads
• Configure and maintain compute clusters for distributed data processing
• Plan capacity and scalability roadmaps to accommodate 100TB+ annual data growth
• Design and implement efficient monitoring and alerting systems to forecast growth trends and proactively react to critical states
• Design, create, automate, and maintain various data pipelines
• Enhance existing and setup new “data checks” and alerts to determine when the data is “bad”
• Design and implement a comprehensive on-premise Data Lake system connected to VAST storage solution for normalized market data across:
  • US Equities, US Futures, and SIP feeds
  • Other market data sources that will be further added
  • Security Definition data for various markets
  • Various private column data
• Build and operate end‑to‑end data pipelines and SLA/SLO monitoring to ensure data quality, completeness, and governance
• Analyze existing data models, usage patterns, and access frequencies to identify bottlenecks and optimization opportunities
• Develop metadata and catalog layers for efficient data discovery and self‑service access
• Design and deploy event‑driven architectures for near real‑time market data processing and delivery
• Orchestrate ETL/ELT data pipelines using tools like Prefect (or Airflow), ensuring robustness, observability, and clear operational ownership
• Ensure fault tolerance, scalability, and high availability across existing systems
• Partner with traders, quantitative researchers, and other stakeholders to understand use cases and continuously improve the usability, performance, and reliability of the Data Lake  

Requirements:

• 5+ years of experience in data engineering or data platform roles
• Proven experience with large‑scale data infrastructure (hundreds of TBs of data, high‑throughput pipelines)
• Strong understanding of market data formats and financial data structures (e.g., trades, quotes, order books, corporate actions)
• Experience designing and modernizing data infrastructure within on-premise solutions
• Bachelor’s degree in Computer Science, Engineering or related field required; Master’s degree preferred or equivalent practical experience

Tech Skills:

• Data Engineering - Spark, Iceberg (or similar table formats), Trino/Presto, Parquet optimization
• ETL pipelines - Prefect/Airflow or similar DAG-oriented tools
• Infrastructure - High-performance networking and compute
• Storage Systems - High-performance distributed storage, NAS/SAN, object storage
• Networking - Low-latency networking (aware about DPDK and kernel bypass technologies. Data center infrastructure basics
• Programming - Python (production‑grade), SQL, building APIs (e.g., FastAPI)
• Data Analysis - Advanced SQL, Tableau (or similar BI tools), data profiling tools

Nice to have:

• Experience in HFT or financial services
• Background in high‑frequency trading (HFT) or quantitative finance

What we offer:

• Competitive compensation package
• Performance-based bonus opportunities
• Healthcare & Sports/gym budget
• Mental health support, including access to therapy
• Paid time off (25 days)
• Relocation support (where applicable)
• International team meet-ups
• Learning and development support, including courses and certifications
• Access to professional tools, software, and resources
• Fully equipped workstations with high-quality hardware
• Modern office with paid lunches
   

Our motivation:

We are a company committed to staying at the forefront of technology. Our team is passionate about continual learning and improvement. With no external investors or customers, we are the primary users of the products we create, giving you the opportunity to make a real impact on our company's growth.

Ready to advance your career? Join our innovative team and help shape the future of trading on a global scale. Apply now and let's create the future together!

Candidates based in Poland are especially welcome. Proficiency in Polish will be a strong advantage. 
 

Scope of Work (Snowflake Data Engineer / Architect)

- Migration of data processing pipelines and datasets between two Snowflake instances. 

- Reverse engineering of selected existing solutions in order to assess the required level of modification (including implementation of selected adjustments). 

- Migration of several Streamlit applications (native Streamlit in Snowflake) alongside the data and pipelines. 

- For selected datasets and pipelines, implementation of new components (code, data structures, and Snowflake cross-account data sharing mechanisms). 

- Re-creation of an existing data processing framework currently used by another business unit on the new Snowflake account. 

- Ensuring that all data structures required for critical applications and Power BI reports are available in the new Snowflake account, including the pipelines/processes feeding those structures. 

-The role will require close collaboration with a Power BI specialist responsible for analyzing and prioritizing semantic models and Power BI reports currently consuming data from the existing Snowflake account.

Primary Skills: 

- SQL

 -Snowflake (preferred) or other cloud data warehouse solutions 

- Data layering 

- Stored procedure / Cursor / Dynamic SQL / Window functions / Recursive Query etc C# development 

- ETL - Azure Data Factory (or other ETL Tools)

- Data pipeline design 

- REST API / Oauth 

- Semi-structured Data 

- File Processing: JSON / XLSX / CSV / PARQUET

We offer:

• Attractive financial package

• Paid vacation, holidays and sick leaves

• Challenging projects

• Professional & career growth

• Great atmosphere in a friendly small team

• Flexible working hours

Responsibilities

Building both batch and streaming pipelines in production environments

Requirements (Must-have)

4-5 years of experience in Data Engineering

Strong experience with Apache Spark (including Structured Streaming)

Experience building both batch and streaming pipelines in production environments

Proven experience designing AWS-based data lake architectures (S3, EMR, Glue, Athena)

Experience with event streaming platforms such as Apache Kafka or Amazon Kinesis

Experience implementing lakehouse formats such as Delta Lake

Strong understanding of partitioning strategies and schema evolution

Experience using SparkUI and AWS CloudWatch for profiling and optimization

Strong understanding of Spark performance tuning (shuffle, skew, memory, partitioning)

Proven track record of cost optimization in AWS environments

Experience with Docker and CI/CD pipelines

Experience with Infrastructure as Code (Terraform, AWS CDK, or similar)

Familiarity with monitoring and observability practices

Nice to Have

Experience in the financial domain

Experience running Spark workloads on Kubernetes

Exposure to or interest in Large Language Models (LLMs) and AI integration

Experience implementing data quality frameworks or metadata/lineage systems

Hiring Process

Intro call

Technical discussion (focused on real experience)

Offer

Start: ASAP