Senior Data Engineer

About the Team

Senior Data Engineer,

This is a unique opportunity to shape the architecture and the tech execution patterns of a green field
ecosystem to create a next-generation advisor and client experience. We're building for scale. As such, much of what we design and implement today will be the technology/infrastructure which will serve thousands of clients and petabyte-level volumes of data.

The core stack we use and are building is:

• AWS as our cloud provider
  • Oracle as our legacy data warehouse• Snowflake as our next-gen data warehouse• Mage AI for data ingestion and processing• Kafka as our message bus• Terraform for building infrastructure

Key Responsibilities

• Work as part of the team to build reliable and scalable pipelines and capabilities across the
  platform, as well as monitor and support the capabilities we offer.• Construct complex architectures tying multiple services, SaaS tooling and third party data together, leveraging a strong understanding of a cloud-based stack.• Contribute to the technical strategy of the team, and its execution through prioritization, and delivery management.• Set high standards across documentation, testing, resiliency, monitoring, and code quality. Enforce these standards by holding your team accountable.• Drive towards efficiency, lower our cloud spend, tackle our tech debt and look for ways to simplify code, infrastructure and data models across the platform.• Write well-rounded, reusable and documented code that captures the essential nature of the solution. • Inspire, teach and guide your fellow team members; lead design sessions, participate in code reviews, take ownership of operational processes.• Promote data quality, governance and security as a first-class citizen of the platform, complying with relevant regulations

Required Skills

• You have at least 6 years of relevant professional experience in Data Engineering • You’ve participated in shaping the architecture of a mature cloud data platform

  (AWS, GCP,

  Azure),

  designed for different consumer types, and providing quantifiable business value.• You have hands-on experience in building resilient batch

  (Airflow, Fivetran, Mage AI, Airbyte) and

  streaming (Kafka, Kinesis, Flink, Spark) data pipelines at scale (> 1 TB/day)

  • You have designed and implemented performant, reusable, and scalable data models in a cloud data warehouse

  (dbt, BigQuery, Snowflake)

  and have working experience with legacy ecosystems

  (Oracle, Postgres)

  • You’ve run PoCs, planned large migrations of data and code, and participated in planning a roadmap multiple times before.• You can build and maintain your own infrastructure through IaC (Terraform, OpenTofu, Ansible), containerization (Docker) and CI/CD (Jenkins, Github Actions); you rely on DevOps expertise when needed• You preach operational procedures from data and infrastructure observability (Monte Carlo, Datadog, Prometheus), alerting and incident management (PagerDuty, incident.io)• You are highly proficient in SQL and Python, and are confident applying them across data engineering tasks• You are a strong communicator and collaborator, able to engage with both technical and non[1]technical teams. You listen actively and contribute constructively.• You’re AI-proficient or AI-curious, eager to explore how emerging technologies can enhance yours and your team’s productivity.• You have experimented with Machine Learning frameworks (TensorFlow, PyTorch, Scikit-learn) and LLM frameworks (e.g. Langchain)

Apply without meeting all requirements statement
If you don’t meet every requirement but believe you’d thrive in this role, we’d still love to hear from you. We're always keen to speak to people who connect with our mission and values.

Location and Travel

The salary range will be determined based on experience, skills, and geographic location.
Equal Opportunity Employer

Invest Cloud is committed to fostering an inclusive workplace and welcomes applicants from all

Preferred candidate profile