DataArt

Client

Our client is a prominent global wealth and asset management firm focused on delivering innovative investment solutions and a networked ecosystem of international opportunities. The organization operates within a highly regulated environment, prioritizing the transformation of complex concepts into actionable financial strategies for a global clientele.

Project overview

The project involves the development and expansion of a centralized, scalable data ecosystem. Having successfully ingested the initial data source, the team is now moving into a high-growth phase to integrate multiple high-value financial and operational data streams. The goal is to provide C-level executives and advisors with a unified, reliable reporting layer for strategic decision-making.

Position overview

As a Senior Data Engineer, you will be a technical cornerstone of the data platform team. You will be responsible for the end-to-end engineering of data pipelines, from ingestion to transformation, ensuring that the Snowflake warehouse is optimized for complex wealth management analytics. You will work at the intersection of sophisticated financial data and enterprise-grade engineering.

Responsibilities

• Design, build, and maintain scalable automated ETL/ELT pipelines to ingest data from diverse sources including Addepar, NetSuite, Salesforce, Morningstar, Bloomberg, and UKG.
• Architect and implement robust data models within Snowflake using DBT (Data Build Tool) to ensure high-performance transformations and clean data structures.
• Utilize Workato to orchestrate seamless integrations between third-party SaaS platforms and the central data warehouse.
• Monitor and optimize Snowflake performance, storage, and compute usage to ensure cost-effectiveness and reliability.
• Partner with Business Analysts and Tableau Engineers to ensure the data layer effectively supports complex business use cases and executive dashboards.
• Implement rigorous data validation and testing frameworks to maintain high data integrity, especially critical given the regulated nature of investment data.

Requirements

• Extensive hands-on experience as a Data Engineer focusing on Snowflake architecture, including advanced performance tuning and security features.
• Proven proficiency with DBT for data transformation and Workato (or similar enterprise integration platforms) for workflow automation.
• Strong ability to understand complex financial datasets and translate business-centric data needs into technical schemas.
• Solid understanding of software engineering best practices, including version control (Git) and CI/CD pipelines for data.
• Exceptional ability to communicate technical concepts effectively with both business stakeholders and cross-functional technical teams.

Nice to have

• Experience supporting reporting requirements for Tableau-based visualization layers.
• Experience within the Wealth Management or Investment Management sector, with specific familiarity handling investment and portfolio-related data.
• Understanding of regulatory requirements regarding financial data handling and privacy.
• Background in integrating market data providers such as Bloomberg or Morningstar.
• Advanced SQL skills and experience with Python for data engineering tasks.

Project overview

The project extensively uses AWS cloud, Lambdas, containers, infrastructure as a code, SQL, and NoSQL storage, and the latest versions of languages and tools. Some teams are more product-oriented and build outstanding student-facing applications, and some teams own shared components and services used by other products.

Responsibilities

• Design, implement, and operate AWS-based infrastructure using Terraform
• Build and maintain scalable serverless and containerized environments (Lambda, ECS, etc.)
• Implement monitoring, logging, and alerting to ensure high system reliability and performance
• Automate operational tasks and workflows using lightweight Python scripts
• Apply best practices for security, availability, and cost optimization in cloud environments
• Support multiple teams by providing stable and reusable cloud components
• Collaborate closely with client and internal stakeholders in an Agile environment

Requirements

• Strong experience with AWS services (Lambda, RDS, DynamoDB, networking, IAM, etc.)
• Hands-on experience with Infrastructure as Code, preferably Terraform
• Solid understanding of Linux-based systems and cloud networking fundamentals
• Experience designing and maintaining monitoring and observability solutions (logs, metrics, alerts)
• Intermediate Python skills for scripting and automation purposes
• Experience working with SQL and NoSQL databases
• Familiarity with Agile/SCRUM development processes
• Good spoken English for daily communication with client-side team members

Client

Our client specializes in delivering comprehensive remote work solutions. Their services cover the complete lifecycle of equipment management, offering onboarding, engagement, retention, and wellness programs tailored to reduce costs for their clients.

Position overview

We are looking for an Experienced Senior DevOps Engineer to take ownership of an advanced AWS infrastructure. This role is crucial in maintaining the current setup and leading the migration to a scalable Kubernetes ecosystem based on GitOps principles.

Responsibilities

• AWS Infrastructure Management: Oversee and optimize the current AWS setup (v1) using ECS, Fargate, CodePipeline, and Terraform, ensuring scalability, security, and cost-efficiency
• Infrastructure as Code (IaC): Manage AWS resources with Terraform and maintain auditable infrastructure changes
• Kubernetes Migration: Lead the migration to Kubernetes (v2) on Amazon EKS using GitOps principles with ArgoCD and Helm
• Kubernetes Tools: Implement tools like Karpenter, Argo Rollouts, Reloader, External-DNS, and External-Secrets for efficient cluster management
• Container Orchestration: Manage containerized applications in ECS/Fargate and optimize performance
• CI/CD Pipelines: Build and maintain CI/CD pipelines with GitHub Actions and AWS CodePipeline, automating testing and deployments
• Programming: Create automation tools with Python or Go to improve operational workflows
• Collaboration: Partner with cross-functional teams and mentor junior engineers on best practices

Requirements

• A background in start-ups is essential for this position
• AWS Certified DevOps Engineer – Professional
• AWS Certified Solution Architect – Professional
• Certified Kubernetes Administrator (CKA)
• Monitoring and logging tools: Prometheus, Grafana, AWS X-Ray
• Network configuration and security within AWS, including account management best practices
• In-depth knowledge of AWS Managed Database Systems (RDS/Aurora)

Project overview

The project focuses on building and evolving a cloud‑based Business Intelligence platform using Qlik Cloud to support enterprise reporting, analytics, and self‑service data exploration. The work emphasizes data modeling, dashboard development, semantic layer design, and ensuring trusted, governed insights for business and operational stakeholders.

Team

You will work in a cross functional team including software engineers, QA specialists, and cloud engineers. The team collaborates in an Agile setup with shared responsibility for infrastructure, delivery pipelines, and platform stability.

Position overview

We are looking for a BI Engineer with hands‑on experience in Qlik Cloud to design, develop, and maintain business intelligence solutions. You will work closely with data, business, and platform teams to transform data into actionable insights, enabling decision‑making across the organization. The role combines strong analytical thinking with BI development, data modeling, and stakeholder collaboration.

Technology stack

Qlik Cloud Qlik Sense SaaS, Qlik Data Integration, SQL, PostgreSQL, SQL Server, Snowflake, BigQuery, Azure Cloud data platform, REST APIs, flat file integrations, Git

Responsibilities

• Design, develop, and maintain Qlik Cloud dashboards, applications, and reports
• Translate business requirements into clear data visualizations and KPIs
• Develop reusable measures, dimensions, and analytical data models in Qlik
• Create and maintain Qlik load scripts to ingest and transform data from multiple sources
• Ensure performance, usability, and scalability of Qlik applications
• Apply Qlik Cloud best practices for governed and self service analytics
• Collaborate with business stakeholders to understand reporting and analytics needs
• Support BI releases, enhancements, and ongoing improvements across environments
• Optimize existing dashboards and data models for clarity and performance
• Contribute to BI standards, templates, and development guidelines
• Stay informed about new Qlik Cloud features and analytics trends

Requirements

• 2 to 5 years of experience in a BI Engineer, BI Developer, or Analytics Engineer role
• Hands on experience with Qlik Cloud Qlik Sense SaaS
• Strong SQL skills and experience working with relational databases
• Experience designing analytical data models and KPIs
• Understanding of data visualization principles and dashboard UX
• Ability to work closely with business users and translate requirements into insights
• Strong analytical and problem solving skills

Nice to have

• Experience with Qlik Data Integration or other ETL or ELT tools
• Exposure to cloud based data warehouses
• Experience with data governance or data quality initiatives
• Basic scripting or automation experience
• Familiarity with CI CD concepts for BI assets
• Experience supporting enterprise or regulated environments

Project overview

The Exposure Platform is a long running enterprise data transformation initiative focused on replacing legacy SQL based logic with modern, scalable data processing solutions. The platform handles large data volumes and supports multiple business domains through a shared and business critical codebase. The work emphasises maintainability, performance, and strong software engineering practices across the organisation.

Team

You will work in a small cross functional data engineering team consisting of senior data engineers and software engineers. The team collaborates closely through code reviews, shared design discussions, and agreed engineering standards while contributing to a common codebase. The team is currently expanding and values structured collaboration and technical ownership.

Position overview

We are looking for a Senior Data Engineer to support a large scale transformation from SQL Server based systems to a Databricks and Delta Lake platform. You will focus on enterprise grade data engineering and software development, building maintainable and scalable data processing solutions used by multiple teams. This role is not focused on analytics or reporting, but on core data transformation and platform development.

Technology stack

Databricks, Delta Lake, Python, PySpark, SQL Server, Azure Data Factory, Azure DevOps, Git, CI CD pipelines

Responsibilities

• Read, understand, and reason about complex SQL stored procedures and embedded business logic
• Redesign and implement existing SQL logic as clean and maintainable Python and PySpark code in Databricks
• Develop production grade transformation code using reusable packages, modules, and components
• Apply software engineering best practices including clean code, object oriented design, modularisation, and refactoring
• Design and evolve data models across Bronze, Silver, and Gold layers
• Work with very large data volumes and highly parallel event driven data transformations
• Participate actively in code reviews and technical design discussions
• Contribute to the stability, scalability, and long term maintainability of the shared data engineering codebase

Requirements

• Strong experience with Python and PySpark in production data engineering environments
• Hands on experience working with Databricks and Delta Lake
• Strong SQL skills with the ability to read, analyse, and translate complex stored procedures
• Experience working in large shared codebases beyond notebook based development
• Solid understanding of object oriented programming and software engineering principles
• Experience applying clean code practices, refactoring, and maintainable design
• Strong background in data modelling, including transactional and analytical models
• Experience working with layered data architectures such as Bronze, Silver, and Gold
• Ability to analyse existing code line by line and explain technical and business logic clearly

Nice to have

• Experience with Power BI for data consumption or validation
• Exposure to enterprise scale data platforms in complex organisational environments