About the company:

Gloat puts people and companies in motion. Our Agile Workforce Operating System is helping the world's most renowned enterprises become dynamic organizations, future-fit for any eventuality, and poised for continuous growth and innovation in today's ever-changing economic climate.

We deliver AI-powered intelligence, infrastructure, and applications that enable organizations to effectively tackle change with agility, unlock capacity and productivity, and reduce workforce risk. Today we support industry leaders around the world including HSBC, Spotify, Nestle, Standard Chartered Bank, Schneider Electric, and many more.

Life at Gloat:

Gloat is a revolutionary startup with a global workforce. We have offices in Tel Aviv, New York City and London and work with customers around the globe. We value collaboration, innovative thinking, and curiosity and we’re looking for bright, driven, and passionate people to grow with us. If you care about empowering businesses and people to reach their potential, you’re in for a fun ride.

As a Data Engineering at Gloat, you will be joining the Data Engineering team in charge of multiple responsibilities across all data-oriented tasks fueling our incredible R&D team.

You will have the freedom to explore and implement the newest technologies and data solutions in the market.

You will work with some of the best, imaginative and friendliest people.

You will learn new things every day and will always find new challenges.

So what are you waiting for? Come help us change the future of work!

• Design, develop, and maintain scalable data pipelines and infrastructure to support the collection, processing, and analysis of large volumes of data.
• Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand data requirements and develop solutions that meet business needs.
• Implement best practices for data governance, security, and quality assurance to ensure the integrity and reliability of our data assets.
• Optimize and tune existing data pipelines and processes for improved performance and efficiency.
• Stay up to date with current best practices in the big data field.
• Mentor and coach other members of the data engineering team, providing guidance and support to help them grow their skills and expertise.

• 5+ years of experience working as a data engineer or similar role, with a proven track record of designing and implementing data solutions – MUST.
• Proficiency in programming languages such as Python, Java, or Scala, with experience building and maintaining data pipelines using frameworks like Apache Spark, Apache Kafka, or similar.
• Strong SQL skills and experience working with relational and non-relational databases (e.g., MySQL, MongoDB).
• Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and familiarity with services like AWS Glue, Google BigQuery, or Azure Data Factory.
• Hands-on experience with ETL/ELT processes, data ingestion, data transformation, data modeling, and monitoring.
• Deep experience of one or more of these technologies: Airflow, dbt, Snowflake, Presto / Trino, Kafka, SQS, Sagemaker, Kubernetes, Argo, Terraform, Debezium.
• Strong communication and collaboration skills, with the ability to effectively work with cross-functional teams and communicate technical concepts to non-technical stakeholders.
• Quick learner, team player, independent, imaginative and motivated individual with a passion for data!

Join us and be part of a dynamic team that revolutionizes the HR Tech Industry through data-driven innovation and excellence!

At Gloat, we believe that building the most important company in the history of human capital begins with having a diverse and inclusive workforce ourselves. This means that we look for individuals who can bring unique strengths, perspectives, skills, and backgrounds to our existing teams. Gloat is proud to be an Equal Opportunity Employer, and does/will not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.