Senior BI Data Engineer at LUSHA USA OPERATION INC
Tel-Aviv, Tel-Aviv District, Israel -
Full Time


Start Date

Immediate

Expiry Date

25 Mar, 26

Salary

0.0

Posted On

26 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Engineering, BI, SQL, Python, Data Warehousing, Dimensional Modeling, ELT Pipelines, Data Quality, Observability, Machine Learning, Airflow, Kafka, Spark, CI/CD, Analytics Engineering, Semantic Modeling

Industry

Software Development

Description
As a Senior BI Data Engineer at Lusha, you’ll join a company where culture isn’t a slogan - it’s our DNA. You’ll be part of a data-driven organization where every voice matters, working at the heart of our BI team to raise the bar for analytical excellence. In this role, you’ll take end-to-end ownership of complex, high-impact BI initiatives, shaping how Lusha measures success, makes decisions, and scales. Your work will directly impact over 1M users worldwide, empowering B2B sales teams to unlock new revenue opportunities and drive sustainable growth. What You’ll Actually Do: Lead the design and evolution of Lusha’s BI data foundations, owning key product and GTM metric definitions and data models Build, scale, and maintain high-quality ELT pipelines and curated datasets (raw → modeled → semantic) that power dashboards and self-serve analytics Collaborate closely with Data Scientists to operationalize machine learning use cases, including feature pipelines and analytical datasets Take senior ownership within the BI team by mentoring peers, reviewing critical work, and promoting best practices in analytics engineering and semantic modeling Own the performance, cost, and reliability of the data warehouse and BI layer by optimizing models, queries, and incremental processing patterns Translate ambiguous business questions into clear, governed metrics and scalable data models, partnering with Product, RevOps/GTM, Finance, and Analytics Establish and maintain strong data quality, observability, and monitoring practices (tests, SLAs, anomaly detection) Drive standardization and automation across the BI development lifecycle, including version control, CI/CD, documentation, and release processes Stay ahead of modern BI and analytics engineering trends, including AI-assisted development, and apply them pragmatically to increase trust and speed Requirements 5+ years of experience in Data Engineering / BI roles, with proven ownership of scalable, end-to-end data ecosystems Expert-level experience with modern data stacks, including Snowflake or Databricks and dbt as a core transformation layer Advanced SQL and Python skills, with hands-on responsibility for CI/CD pipelines, data quality frameworks, and observability Deep understanding of dimensional modeling, data warehousing patterns, and semantic layer design Hands-on experience with orchestration tools such as Airflow, managing complex and high-availability ELT workflows Experience working with large-scale data processing, including exposure to Kafka, Spark, or streaming architectures Strong ability to independently lead cross-functional initiatives and translate business requirements into executable technical solutions Strong business and analytical mindset, with an AI-forward approach and curiosity for emerging tools and methodologies Why Lusha: Founded in 2016, Lusha grew from a bootstrapped startup into a $1.5B unicorn, backed by ~$240M in investments Trusted by global leaders like Google, Zendesk, and Yotpo as a leading AI-powered sales intelligence platform Over 1M users, 200M+ data entries, and 40K new signups every month—with massive scale and impact A company built on simplicity, collaboration, trust, and continuous learning Real ownership, real influence, and real opportunities to grow as the company scales At Lusha, your work matters, your voice is heard, and your growth is part of our journey.

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Responsibilities
The Senior BI Data Engineer will lead the design and evolution of Lusha’s BI data foundations and take ownership of complex BI initiatives. This role involves building and maintaining high-quality ELT pipelines and collaborating with Data Scientists on machine learning use cases.
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