Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 4 days ago

Data Platform Engineer

ibgllc180 open roles

Where
Greenwich, CT, USA
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowData Platform Engineeribgllc · Greenwich, CT, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on ibgllc's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 4 days ago

The posting

This is Hybrid role (3 days in office /2 days remote) About your Team: The Enterprise Architecture organization is looking for a Senior Data Platform Engineer to join the team and help build the next generation of data infrastructure and AI-enabled workflows. In this role, you will design, build, and operate the scalable data lake platform, cloud infrastructure, and self-service tooling that internal teams across IBKR rely on to ingest, govern, and analyze data at scale. You will partner closely with internal development teams and IT leadership to architect platform solutions for diverse use cases across the organization, ranging from cloud-native data lakes and infrastructure as code to AI knowledge bases and advanced analytics. Your work will focus on delivering robust, well-documented data platform capabilities and establishing best practices for data engineering and platform operations across the enterprise.    What will be your responsibilities within IBKR: 

Design, build, and operate the data lake platform and infrastructure, including S3-based storage and the AWS Glue data catalog, delivered as a governed, self-service platform that internal teams can build on Design and implement data governance and fine-grained access control across the platform using AWS Lake Formation, ensuring secure, least-privilege, and compliant access to data domains Automate infrastructure provisioning as code (e.g., Terraform), giving internal teams a repeatable, self-service path to stand up new platform resources Contribute to the GenAI knowledge base platform and Python-based services that internal teams use to build retrieval-augmented (RAG) and knowledge-driven AI applications Build or contribute to real-time streaming data pipelines (e.g., using Kafka) for event-driven analytics and data processing, as platform needs evolve Build and maintain scalable ETL/ELT pipelines and data crawlers to ingest data from various sources, transforming structured, semi-structured, and unstructured data (text, images, audio, video) for analytics and AI/ML workloads Monitor, troubleshoot, and continuously optimize the platform for performance, reliability, data quality, and cost efficiency, treating observability as a core platform capability Collaborate with internal development teams, data scientists, and stakeholders to understand requirements, architect platform solutions, and enable teams through clear standards and technical documentation Write clean, maintainable, well-tested code following software engineering and data engineering best practices

   What required skill’s you need: Core Data Platform & Cloud Engineering

5+ years of hands-on data engineering or data platform experience, including building infrastructure, platforms, or tooling used by other engineering teams Strong experience with AWS cloud services, particularly S3, AWS Glue, Athena, and EMR Experience with data governance and fine-grained access control, including AWS Lake Formation Experience with infrastructure as code (e.g., Terraform) to build and manage cloud infrastructure and governance in a versioned, repeatable way Solid understanding of data lake architectures, cataloging, and partitioning strategies Proficiency in Python, with experience building and maintaining scalable ETL/ELT pipelines for data processing and automation Experience with PySpark on EMR for large-scale data processing Strong SQL skills for data analysis and transformation Experience with CI/CD practices, version control (Git), and containerization (Docker)

  AI/GenAI Platform

Foundational understanding of GenAI concepts such as RAG architectures, vector databases, or semantic search, with willingness to build deeper hands-on expertise Familiarity with AWS AI/ML services (e.g., Bedrock, SageMaker) or equivalent tools

  Good to have

Experience with modern table formats (e.g., Iceberg) and schema evolution at scale Experience with Kafka or other streaming platforms for real-time data pipelines Experience with Kubernetes/EKS and workflow orchestration tools (e.g., Airflow, AWS Step Functions, Managed Airflow) Experience with observability engineering (e.g., CloudWatch, Elastic/ELK stack) Experience with data quality frameworks and tooling (e.g., Glue Data Quality) Background in building knowledge management systems or enterprise search solutions Experience in financial services or other regulated data environments

     To be successful in this position, you will have the following:

Self-motivated and able to handle tasks with minimal supervision. Superb analytical and problem-solving skills. Excellent collaboration and communication (Verbal and written) skills. Outstanding organizational and time management skills.

   Company Benefits & Perks

Competitive salary, annual performance-based bonus, and stock grant awards 401(k) retirement plan with competitive company match Excellent health and wellness benefits, including medical, dental, and vision benefits. 100% employer-paid medical premiums, with generous employer contributions to dental & vision plans as well. Wellness screening and assessments, health coaches, and counseling services through an Employee Assistance Program (EAP) Generous paid parental leave (up to 16 weeks paid parental leave for eligible employees) Company-paid basic life insurance, accidental death & dismemberment (AD&D), and short- and long-term disability coverage Flexible Spending Accounts (Healthcare, Dependent Care, and Commuter FSAs) Quarterly fitness stipend to offset costs associated with traditional gym and fitness memberships or fees Education reimbursement and professional development opportunities Legal services, telehealth access, and voluntary insurance options Backup child and adult care support through Care.com Daily lunch allowance and fully stocked kitchen with healthy breakfast and snack options

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against ibgllc's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on ibgllc's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    ibgllc's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.