Senior Data Engineer, Algolia

Salary not provided

SQL

AWS

Docker

GCP

Python

Airflow

Terraform

Azure

Redshift

Spark

Snowflake

BigQuery

dbt

Senior and Expert level

Paris

Remote from France

More information about location

AI search solutions

Job no longer available

AI search solutions

501-1000 employees

B2BArtificial IntelligenceEnterpriseAnalyticsBusiness IntelligenceAPIeCommerce

Job no longer available

Salary not provided

SQL

AWS

Docker

GCP

Python

Airflow

Terraform

Azure

Redshift

Spark

Snowflake

BigQuery

dbt

Senior and Expert level

Paris

Remote from France

More information about location

501-1000 employees

B2BArtificial IntelligenceEnterpriseAnalyticsBusiness IntelligenceAPIeCommerce

Company mission

To help businesses and developers understand their online users and show them exactly what they need.

Job

Company

Role

Who you are

8+ years of experience in data engineering
Expertise with cloud platforms (AWS, GCP, or Azure)
Expertise with orchestration systems (Airflow, Dagster, or similar)
Expertise with data lakes and warehouses (Databricks, Snowflake, BigQuery, or Redshift)
Strong Spark and SQL skills
Familiarity with infrastructure tools (Terraform, Docker)
Familiarity with coding best practices (Python, unit testing, CI)
Awareness and interest in data engineering and modern development
Motivation to build a state-of-the-art platform
Motivation to work in a team-oriented culture
Excellent communication skills
Familiarity with BI tools (ThoughtSpot, Hex)

Desirable

Familiarity with dbt or similar frameworks

What the job involves

Join Algolia’s Data Engineering team. We gather data across all company domains and build and maintain the infrastructure and services that power internal analytics for analysts, data scientists, product managers, and engineers
We are the internal eyes of the company, a critical, central team for Algolia and its business. We aim to build a state-of-the-art data platform and stay alert to new technologies to keep modernizing
We have started a transition from Redshift to Databricks to modernize the platform and scale for the future. The foundation is new. There is still a lot to build and many interesting challenges
Be a key contributor in a mature data engineering team composed of senior engineers
Design, build, and operate reliable batch and streaming pipelines
Improve orchestration, testing, observability, and cost efficiency
Interact with many stakeholders across Product, Engineering, and Analytics
Take strong ownership of what you build and maintain
Share your expertise with other technical teams
Team’s current stack:
AWS infrastructure
S3 data lake
Databricks SQL Warehouse and Workflows
Airflow (MWAA)
Kafka for real time
AWS Glue, EMR, Kinesis
Redshift and Athena (being replaced by Databricks)

Application process

Please submit your application with an English written CV/Resume to ensure our team can effectively review your application

Our take

While in-site searching has been available for some time from web search servers such as Google and Bing, its functionality is limited due to it relying on general web scraping techniques which can miss relevant information. By contrast Algolia indexes only the company's site, allowing its search to serve accurate results extremely swiftly, which helps to drive sales conversions aside from making sites far more usable. The efficacy of this solution can be seen from its customer base of over 10,000 companies including the likes of Slack, Zendesk and Lacoste.

To diversify and increase the product range, Algolia have expanded into other real-time APIs such as product recommendations available for eCommerce websites. With the company performing extremely well over the last few years, Algolia have recruited key senior executives to further its growth. As the company continues to scale it seems likely that an IPO is not too distant a prospect.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

33% female employees

-3% employee growth in 12 months

Glassdoor (3.7)

Company

Funding (last 2 of 7 rounds)

Jul 2021

$150m

SERIES D

Oct 2019

$110m

SERIES C

Total funding: $334m

Company HQ

Barron Park, Palo Alto, CA

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