Company Description
Elephant Ventures builds agentic AI systems for complex enterprises. With a primarily US customer base, Elephant is a fully distributed services company that efficiently marries US product and engineering account leadership while seamlessly leveraging international execution teams in the Philippines, Kenya and New Zealand.
Our core competency lies in leveraging cutting-edge technologies to develop innovative solutions that drive business growth and transformation. Our culture and staff are fearless in the face of complexity and have been dependably delivering high-risk, high-velocity wins and business value for our clients for 2 decades.
Dependability: Taking personal responsibility, showing up and following through
Courage: Being bold, doing what's right instead of what's easy, challenging the status quo
Agility: Being open minded, adjusting course as new information arises
Curiosity: Always learning, exploring what is possible if we put our minds to it
Passion: Enthusiasm and pride about being engineering-led and driving innovation
What Matters Most to Us
We evaluate for core engineering ability and learning speed first — not an exact stack match. The specific tools listed below reflect what our current projects need; they will shift as our project mix shifts, and we don't expect you to already know all of them.
We're looking for people who:
- Have solid computer science fundamentals and can reason clearly about how software and data systems work, not just which tool they've used
- Learn fast — can become productive in an unfamiliar stack or codebase in days to weeks, not months
- Are self-starters who take initiative in ambiguous, fast-changing environments rather than needing detailed direction
- Genuinely want to work with AI/agentic tooling as a daily part of how they build software — using it productively while catching its mistakes
- Communicate clearly with both technical and non-technical stakeholders, including clients, across time zones
About This Role
Elephant Ventures is seeking a Data Engineer II to join our data engineering practice. In short, this engineer owns a feature or pipeline end-to-end, with minimal supervision.
This role is the mainstay of the department — the people working the tasks and stories to meet sprint goals and deliver quality products for our clients. They have core competency in their track and own features or pipelines end-to-end, delivering production quality work with minimal to no supervision, following EV practices and supporting their teammates.
What this looks like in the EV context:
- Engineering Foundation: Owns a feature or a pipeline end-to-end within their track. Makes sound local design, API/schema and data-modeling calls; writes meaningful tests (not just the happy path); handles common security / data-quality pitfalls; debugs systematically across a service.
- AI Orchestrator: AI is a daily, productive habit — sets up context (relevant files, types, conventions), tests AI output as routine, catches AI mistakes (wrong API, hallucinated package, missing edge case), and can say what they deliberately don't delegate and why.
- Fast Learner: Becomes productive in a new stack in days-to-weeks via a repeatable method. Reads unfamiliar code independently (finds entry points, traces execution). Knows when to dig versus ask.
- Collaboration: Understands and executes tech approaches independently; communicates clearly; gives and receives code-review feedback constructively; beginning to offer technical guidance to newer teammates.
- Proactively engages stakeholders and represents the team's technical work with dependable delivery against commitments.
About You
The ideal candidate is someone who's ready for the next challenge with advanced interpersonal and communication skills as you'll be interfacing with the clients and working with a globally distributed team.
General Expectations
- Own & execute EV best engineering practices as a dependable member of an EV project team.
- Observe Agile Scrum best practices
- Actively participate and contribute to Project Team sprint story planning and retro.
- Account for time zone differences as a globally distributed team by proactively communicating in order to deliver best possible work.
- Exhibit client/stakeholder awareness and dependable delivery against commitments.
- Commitment to a high learning velocity
Engineering Skills
ENGINEERING FOUNDATION
- Proficient in Python (pandas); fluent SQL (window functions, CTEs, query optimization); sound modeling (star schema, SCD)
- Owns a pipeline end-to-end; batch + basic streaming/CDC; dbt; orchestration (Airflow/Dagster): schedules DAGs, basic retries/backfills
- Handles late/bad data; data-quality checks; aware of data contracts
- Aware that clean, well-modeled data feeds AI/RAG systems (pgvector a plus)
- Cloud object storage + a cloud warehouse (Redshift/BigQuery/Snowflake); cost-aware querying; lakehouse (Iceberg/Delta) awareness a plus
- Basic operational readiness (logging, monitoring, alerting); CI/CD + Docker (IaC a plus); Git + code review
AI ORCHESTRATOR
- AI is a daily habit and tool usage (eg leverages AI assistance on well-scoped tasks)
- Sets up context
- Routinely tests output
- Catches mistakes in code/SQL (wrong columns, bad joins)
- Knows what not to delegate.
Other Requirements
Problem-Solving Skills:
- Ability to analyze complex technical problems and provide effective solutions
- Ability in identifying and mitigating technical risks in software solutions
Communication Skills:
- Ability to communicate effectively with technical and non-technical stakeholders
- Ability to account for time zone differences by proactively communicating and managing work across remote project teams.
High Learning Velocity
- Becomes productive in a new tech stack within days to weeks using a repeatable method, and can read and navigate unfamiliar code independently.
Collaboration
- Gives and receives code review feedback constructively, and is able to guide and support newer teammates.
Preferred Education and Experience
- Bachelor's Degree in Computer Science or equivalent experience in a relevant field
- At least 2 years experience working on agile software engineering projects
- Certifications: Scrum and/or Cloud data/analytics certification
