Tech Onboarding Engineer for IFS Logistics, a six‑month fixed‑term engagement focused on integrating carriers and providers into the IFS Logistics platform.
Responsibilities
Connect new carriers and providers through APIs and file feeds, including credentials, testing and go‑live support.
Map, clean and validate customer ERP exports, shipment files and invoices into our data model.
Own onboarding tasks for named customers against clear delivery dates.
Support the Product Operations team as they onboard customers and handle master data management.
As a Google Data & AI Engineer (Associate Manager), you will deliver data platforms, analytics, and AI solutions on Google Cloud, owning end-to-end execution from data ingestion and modelling to ML/GenAI and consumption. You will shape solutions with clients and Google partners, lead a small team, and ensure production-ready quality, security, reliability, performance, and cost. You will stay hands‑on in architecture and development while driving DataOps/MLOps, CI/CD, and IaC.
Responsibilities
Hands‑On Data & AI Engineering: Design, build, test, and deploy data pipelines, analytics, and ML/GenAI solutions on Google Cloud, from requirements to production support.
Client‑Facing Solutioning: Work with clients to understand business and data challenges, translate requirements into target‑state data and AI architectures, and act as a trusted technical advisor.
Team Leadership & Collaboration: Manage and mentor on‑shore/off‑shore teams, conduct design and code reviews, and collaborate with data owners, product, security, and business teams.
Modern Engineering & Agile Delivery: Apply DataOps/MLOps, Terraform, automated testing, and CI/CD in an Agile model to deliver quality solutions at pace.
Delivery Governance & FinOps: Own data quality, SLAs, lineage, access control, and cloud cost (BigQuery slots/reservations, storage tiers) of delivered solutions.
Requirements
Nice to have: Google Cloud Professional Data Engineer
Nice to have: Google Cloud Professional ML Engineer
Nice to have: Google Cloud Professional Architect
Nice to have: Looker
Early Careers Internship Program Investments –Data Engineer or Quant Developer (80-100%)
A 6-month internship for a Quant Data Engineer to build backend systems, data pipelines, and front-end dashboards for financial indices and portfolio analytics.
Compensation
Paid internship: we offer standardized salary for all early career interns including free lunch.
Responsibilities
Design and implement a fully automated pipeline to ingest daily index position files and futures price feeds
Create automated monitoring tools, error handling, and data-integrity checks (DataOps)
Translate financial concepts into Python code for portfolio construction, factor models, and risk/return metrics
Build interactive digital dashboards using Streamlit, Plotly Dash, or Shiny
Requirements
Advanced student (Master/PhD) or recent graduate in Computer Science, Physics, Data Science, Mathematics, Quantitative Finance, or a related field
Enrolled in a Bachelor’s or Master’s program, or graduated within the last two years
We are looking for a motivated, analytical, and autonomous Quant Data Engineer Intern who can bridge the gap between financial data and institutional-grade infrastructure. The role involves building the backend, data pipelines, and front-end for portfolio analytics and visualization.
Responsibilities
Design and implement a fully automated pipeline to ingest daily index position files, alongside futures price feeds from premium financial vendors (e.g., Bloomberg, Datastream) into our Snowflake database.
Create a bulletproof daily process (DataOps) including automated monitoring tools, error handling, holiday calendars, and data-integrity checks.
Translate financial concepts into Python code for portfolio construction methodologies, factor models, risk/return look-through metrics, and contribution analysis.
Build an interactive digital dashboard (e.g., using Streamlit) to visualize index data, look-through allocations, and risk metrics.
Requirements
Master/PhD or recent graduate in Computer Science, Physics, Data Science, Mathematics, Quantitative Finance, or a related field
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