Senior BI Data Engineer at NICE

Raanana, Center District, Israel -

Full Time

Start Date

Immediate

Expiry Date

01 Aug, 26

Salary

0.0

Posted On

03 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Snowflake, Python, SQL, dbt, Fivetran, Airflow, AWS, Azure, API Integration, Data Modeling, Data Pipelines, Cloud Data Warehousing, Data Quality, Business Intelligence, Data Governance

Industry

Software Development

Description

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you. So, what’s the role all about? The R&D Business Operations team is responsible for collecting, analyzing, and managing R&D data, change requests, and various cross-unit projects and initiatives. As a BI Data Engineer, you will be the backbone of our data infrastructure owing end-to-end data pipelines that power the analytics and dashboards used across the R&D group, connecting a wide range of data sources into a coherent, scalable platform. You will accompany the full data journey, from ingestion and transformation through to the creation of datasets and, where needed, venture into the reporting and dashboard layer to deliver complete, business-ready data products. We are looking for a seasoned, self-driven professional with a strong sense of ownership who can take a task from start to finish independently. We also value genuine intellectual curiosity — someone who keeps up with what's happening in the data and AI space, is willing to experiment, and helps the team identify where new technologies can create real value How will you make an impact? • Design, build, and maintain scalable data pipelines feeding dashboards and analytical products across the R&D organization • Own and manage the cloud data warehouse — schema design, performance tuning, and access control • Manage data ingestion workflows connecting diverse data sources to the central data platform • Develop and maintain transformation models ensuring clean, well-documented, and tested data layers • Accompany the full data lifecycle from raw ingestion to business-ready datasets, and build the corresponding reports and dashboards where needed • Implement data quality checks, monitoring, and alerting to proactively identify and resolve issues • Translate business requirements into data solutions, working across R&D, Product, IT, and Business Operations • Explore emerging AI capabilities as they relate to data engineering and help identify practical opportunities for the team Have you got what it takes? • At least 5 years of hands-on, production data engineering experience • Proven expertise with a cloud data warehouse (Snowflake) • Hands-on experience with a data ingestion tool (e.g., Fivetran or equivalent) • Hands-on experience with a data transformation framework (e.g., dbt or equivalent) • Strong SQL skills: advanced querying, optimization, and data modeling • Strong hands-on experience working with external APIs, including authentication, rate limits, pagination, and error handling • Ability to design, build, and maintain custom API-based data ingestion pipelines in Python • Hands-on experience with Python for data engineering tasks • Practical experience operating workflow orchestration tools such as Airflow • Ownership and administration of cloud data environments such as AWS or Azure, including account-level responsibility for data workloads • A strong sense of accountability — comfortable being the go-to person for your data domains and available to respond when issues arise outside of regular hours • Genuine curiosity about developments in the AI and data space — someone who actively follows trends, is eager to experiment, and brings new ideas to the table You will have an advantage if you also have: • Familiarity with BI and reporting tools • Experience with R&D tooling ecosystems • Exposure to data governance or data observability practices • Fluent English — written and spoken What’s in it for you? Join an ever-growing, market-disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr! Enjoy NiCE-FLEX! At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. #LI-Hybrid Requisition ID: 10660 Reporting into: Director, R&D Operations, CX Role Type: Individual Contributor About NiCE NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions. Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries. NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.

Responsibilities

The role involves designing, building, and maintaining scalable data pipelines and managing the cloud data warehouse to support R&D analytics. You will oversee the end-to-end data lifecycle, from ingestion and transformation to the delivery of business-ready datasets and dashboards.