[Remote] Senior Data Platform Engineer at Dataiku

London, England, United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

TechnologyIndustries

Requirements

Expert level engineering within the Dataiku Platform including Platform Automation, GenAI Capabilities, Plugin Development, maintenance & troubleshooting
Expert level engineering within Snowflake for data engineering and security/governance features
Strong software development lifecycle knowledge and DataOps skills
Proficiency in Python & SQL (among other languages)
Excellent verbal and written communication skills
Sharp analytical mind
Positive attitude towards work
Thrives when collaborating towards a shared goal
Naturally curious
Strong non-technical skills, learning & teaching, and business acumen

Responsibilities

Be an expert level engineer within the Dataiku Platform including Platform Automation, GenAI Capabilities, Plugin Development, maintenance & troubleshooting
Be an expert level engineer within Snowflake for data engineering and security/governance features
Build & maintain GenAI Platform solutions focused on security and governance for engineering delivery
Build & maintain Python & SQL based platform automation process
Build & maintain DataOps process for SDLC delivery
Build & maintain data quality metrics & observability to help drive data quality standards
Build & maintain administration systems and applications for monitoring, alerting, data observability, access management, platform metrics, and end user transparency
Assist Data Engineering with building python & SQL data replication & data pipelines on large & often complex data sets
Design data models for both short term and long term use cases to support data warehouse scalability
Identify opportunities for improvements & optimization for greater scalability & delivery velocity
Collaborate with engineers within GenAI Engineering & Analytics Engineering to build scalable solutions within the Data Platform
Perform root cause analysis on often complex errors to help ensure data pipeline availability
Help drive technical & architectural decisions on the data platform including decisions on data architecture

Skills

Key technologies and capabilities for this role

SnowflakeDataikuGitHubPythonSQLGitHub ActionsDataOps

Questions & Answers

Common questions about this position

What are the key technical skills required for this Senior Data Platform Engineer role?

The role requires expert-level engineering in Dataiku Platform including automation, GenAI capabilities, and plugin development; expert-level Snowflake for data engineering, security, and governance; proficiency in Python and SQL for platform automation; and strong software development lifecycle knowledge with DataOps skills using Github Actions.

What non-technical skills are important for this position?

Non-technical skills such as learning & teaching, business acumen, excellent verbal and written communication, a sharp analytical mind, natural curiosity, positive attitude, and thriving in collaboration are critical.

Is this role remote or does it require office presence?

This information is not specified in the job description.

What is the salary or compensation for this position?

This information is not specified in the job description.

What kind of company culture or team environment can I expect?

The role is part of the Enterprise Data and Analytics (EDA) team, collaborating with centralized analytics, embedded analytics teams, and self-service users; every Dataiker is encouraged to use the company's own product, fostering a collaborative environment focused on shared goals.

Dataiku

AI solutions for operationalizing business processes

About Dataiku

Dataiku develops AI solutions aimed at integrating artificial intelligence into everyday business operations. Their products focus on operationalizing AI, which helps businesses enhance their processes and outcomes. Key offerings include Generative AI, which creates new content or predictions, and MLOps, which facilitates collaboration between data scientists and operations teams to manage the machine learning lifecycle. Dataiku's solutions have proven effective, as demonstrated by their work with a retail client that improved forecast runtime by 900% with high accuracy. The company generates revenue by providing these AI solutions and has a partnership with AWS, enhancing their service offerings and scalability for clients.

New York City, New YorkHeadquarters

2013Year Founded

$823.3MTotal Funding

SERIES_FCompany Stage

Data & Analytics, AI & Machine LearningIndustries

1,001-5,000Employees

Benefits

Health, life & pension benefits

Equity

Time off for R&R

Public holidays

Work from anywhere policy (unique to team)

12 weeks of paid parental leave

Volunteering opportunities

Career Development opportunities

Technology stipend

Onsite meals & healthy snacks

Office happy hours

Company-wide events

Risks

Competition from AI platforms like Databricks may impact Dataiku's market share.

High costs of generative AI initiatives could strain client budgets.

Reliance on partnerships poses risks if collaborations face challenges.

Differentiation

Dataiku offers a centralized platform for enterprise AI and data analytics.

The company integrates with AWS, enhancing connectivity and scalability for clients.

Dataiku's LLM Guard Services ensure controlled Generative AI rollouts.

Upsides

Dataiku's partnership with Rower Consulting expands its reach in the pharmaceutical sector.

Recognition in Gartner's Magic Quadrant boosts Dataiku's credibility in AI solutions.

Dataiku Stories enhances user engagement with Generative AI-powered presentations.

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