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Data Engineer
DATAIKU New York, NY
$115k-141k (estimate)
Full Time 2 Months Ago
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DATAIKU is Hiring a Data Engineer Near New York, NY

Dataiku is looking for a Data Engineer to join our Enterprise Data and Analytics (EDA) team. As a member of the EDA Team, you will play a central role in delivering data to fuel analytics and data-driven insights to various stakeholders and teams within the company. You will also be a key technical member contributing to the Data Platform that fuels centralized analytics, embedded analytics teams, and self service users across the organization. At this level of seniority, non-technical skills, learning & teaching, and business acumen are critical, along with the expectation of technical excellence as you will help drive technical decision making and solutioning of key technical challenges both within the team and across the Analytics Community.

The Data Engineering day-to-day will primarily be within the Data Platform built using Snowflake, Dataiku & Github. The primary development will focus on python & SQL (among other languages), DataOps processes built within Github Actions & Dataiku, and data platform processes built within Snowflake & Dataiku. Strong software development lifecycle knowledge and DataOps skills are a must! The ideal candidate is naturally curious, has excellent verbal and written communication skills, a sharp analytical mind, a positive attitude towards work and thrives when collaborating towards a shared goal. This is an internal and non-client facing role.

How you’ll make an impact 

Dataiku is unique in that every Dataiker is encouraged to use our own product within our Enterprise Data Platform. That means this is a unique opportunity to deliver a scalable platform with governed data to fuel an entire company of current or potential Data Analysts! Your responsibilities within the team include but are not limited to:

  • Be an expert level engineer within the Dataiku Platform 
  • Be an expert level engineer within Snowflake for data engineering and security/governance features
  • Build & maintain python & SQL data replication & data pipelines on large & often complex data sets 
  • Build & maintain data quality metrics & observability to help drive data quality standards
  • Design data models for both short term and long term use cases to support data warehouse scalability
  • Build & maintain administration systems and applications for monitoring, alerting, data observability, access management, platform metrics, and end user transparency
  • Identify opportunities for improvements & optimization for greater scalability & delivery velocity
  • Collaborate closely with Analytics Engineers to provide data & data models for analytical deliverables
  • 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, data engineering processes, data quality frameworks, data access security & governance frameworks, DataOps processes & data consumption models.
  • Help test new features in Dataiku and partner tools to both provide feedback internally as well as determine value towards internal analytics & data platform integration
  • Work closely with key stakeholders across the organization including Infra, embedded analytics teams, Product and Engineering to help foster both technical implementations & requirements gathering
  • Promote the Data Platform internally, help train & mentor others within the organization with technical excellence, & provide support on data & platform related inquiries
  • Proactively drive innovation internally with dedicated innovation time & projects that aim to be transformational for either the platform, team or company as a whole.
  • Actively contribute to the expertise level and competencies of the EDA Team and participate in the creation and support of data development standards and best practices. 

What you’ll need to be successful

  • 3-4 years' of relevant experience in Data Engineering / Data Platform Engineering / Data Architecture
  • Expertise in SQL & Python is a must. Experience in Dataiku DSS is a big plus. 
  • Prior experience with Snowflake strongly desired
  • Prior experience with DevOps technologies such as Github Actions, Azure DevOps or Jenkins
  • Strong understanding of data architecture & data modeling concepts
  • Location: Must be currently located within the EST or CST regions of the United States. Open for candidates based in the UK, if they have the right skillset.

What will make you stand out

  • Prior experience building and maintaining replication & data pipelines in a cloud data warehouse or data lake environment
  • Excellent analytical and creative problem-solving skills - exhibit confidence to ask questions to bring clarity, share ideas and challenge the norm.
  • Passion for continuous learning and teaching to help learn & teach new technologies & implementation strategies
  • Experience working with complex stakeholders; dissecting vague asks and helping to define tangible requirements
  • Ability to manage multiple projects and time constraints simultaneously in a high trust remote environment
  • Ability to wear multiple hats depending on the project with the focus on accomplishing end goals while inspiring colleagues to do the same
  • Excellent written and verbal communication skills (especially with senior level stakeholders) with the ability to speak to both the business value, data products, & technical capabilities of a platform. Ability to create clear and concise documentations with a high degree of precision

#LI-Remote

Job Summary

JOB TYPE

Full Time

SALARY

$115k-141k (estimate)

POST DATE

07/13/2024

EXPIRATION DATE

08/23/2024

WEBSITE

dataiku.com

HEADQUARTERS

New York, NY

SIZE

200 - 500

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If you are interested in becoming a Data Engineer, you need to understand the job requirements and the detailed related responsibilities. Of course, a good educational background and an applicable major will also help in job hunting. Below are some tips on how to become a Data Engineer for your reference.

Step 1: Understand the job description and responsibilities of an Accountant.

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The data engineer develops and maintains the enterprise data framework for continued use.

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Step 2: Knowing the best tips for becoming an Accountant can help you explore the needs of the position and prepare for the job-related knowledge well ahead of time.

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Changing oil, running basic checks, topping off fluids and checking tire pressure are common job duties.

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Oil changes are an essential component of preventative maintenance.

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A data engineer should be aligned with a data scientist’s needs while creating a data system.

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Start with an entry-level position.

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Consider pursuing additional professional engineering or big data certifications.

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Step 3: View the best colleges and universities for Data Engineer.

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