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Lusha

Data Analytics Engineer

Posted 2 Days Ago
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Remote
Hybrid
Hiring Remotely in Tel Aviv
Mid level
Remote
Hybrid
Hiring Remotely in Tel Aviv
Mid level
Seeking a Data Analytics Engineer to build and maintain data infrastructure, optimize data pipelines, and collaborate on data requirements to support business intelligence and product analytics.
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Description

Who we are 

Founded in 2016, Lusha grew from a bootstrapped startup to a $1.5B unicorn, backed by $245M in investments and trusted by sales teams at Google, Zendesk, and Yotpo. 

Lusha is an AI-powered sales intelligence platform, changing the B2B sales experience with a new approach called Sales Streaming. Allowing salespeople to spend most of their time selling instead of wasting time and effort on manual prospecting.

With 1.5M+ users, 200M+ contacts, and 40K new signups every month, we’re the engine behind modern GTM teams. And we’re just getting started.

Where does this role fit in our vision?

Every role at our company is designed with a clear purpose—to integrate collective efforts into our shared success, functioning as pieces of a collective brain. We are seeking a skilled Data Analytics Engineer to join our dynamic Analytics team. In this role, you will play a critical part in building, maintaining, and scaling our data infrastructure to support business intelligence, product analytics, and business operations. You will collaborate closely with analysts, data scientists, and cross-functional stakeholders to ensure clean, reliable, and efficient data pipelines. This is an opportunity to contribute to a data-driven culture and help drive actionable insights across the company.

What will you be responsible for?

  • Designing, building, and optimizing robust data pipelines to ingest, process, and store data from various sources
  • Maintaining and optimizing our data warehouse (e.g., Snowflake, BigQuery, Redshift) and building data models to ensure scalability, reliability, and performance
  • Developing and maintaining ETL/ELT workflows to enable data accessibility for reporting and analysis
  • Collaborating with analytics teams (BI, product, and business) and cross-functional teams (GTM, product) to understand data requirements and providing the necessary infrastructure and data models to support their objectives
  • Monitoring and troubleshooting data quality, pipeline failures, and performance issues, and implementing fixes and improvements as needed
  • Contributing to automating manual processes and improving data reliability and efficiency
  • Staying up-to-date with emerging trends, tools, and technologies in data engineering to drive innovation and continuous improvement

Here’s what we need from you:

  • 3+ years of experience in a data engineering role, with a proven track record of building and managing data pipelines and infrastructure.
  • Good understanding of data warehousing concepts such as dimensional models, database design, and data modeling
  • Strong business understanding and ability to analyze data
  • Strong proficiency with SQL for data manipulation and querying.
  • Hands-on experience with ETL/ELT tools (e.g., dbt, Apache Airflow)
  • Experience with cloud platforms such as AWS, GCP, or Azure, including data-related services (e.g., S3, Redshift, BigQuery, Data Lake, Snowflake).
  • Familiarity with programming languages such as Python
  • Knowledge of tools and frameworks for big data processing (e.g., Apache Spark, Kafka, Databricks) is a plus.
  • Strong problem-solving skills, attention to detail, and ability to work independently and collaboratively in a fast-paced environment
  • Excellent communication and interpersonal skills.
  • AI-savvy: comfortable working with AI tools and staying ahead of emerging trend

We’re dreamers, innovators, and learners, driven by simplicity, collaboration, and trust.

At Lusha, your work matters. Your voice is heard. And your growth is part of our growth.

Ready to join us? Let’s build the future of sales, together.



Requirements
None

Top Skills

Apache Airflow
Spark
AWS
Azure
BigQuery
Data Lake
Databricks
Dbt
Elt
ETL
GCP
Kafka
Python
Redshift
S3
Snowflake
SQL

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