Data Engineer

Description

About the company:

Gloat puts people and organizations 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.

About the Role

We’re looking for a Data Engineer with a passion for analytics to join our growing data team! This role is ideal for someone who enjoys working across the entire data pipeline.

From data ingestion and transformation, all the way to creating analytics-ready datasets.

You’ll get hands-on experience with modern tools, collaborate across functions, and help deliver data-driven insights that shape key decisions.

You’ll be part of a supportive team, where mentorship, impact, and learning go hand in hand.

Responsibilities

What You’ll Do:

• Design, develop and maintain end-to-end data pipelines: extract raw data from sources such as MongoDB, MySQL, Neo4j, and Kafka; transform and load it into our Snowflake data warehouse.
• Contribute to data modeling and data quality efforts to ensure reliable, analytics-ready datasets.
• Collaborate with analytics, engineering, and business teams to understand data needs and translate requirements into actionable data solutions.
• Enable data-driven decisions by building dashboards and reports using tools like dbt and AWS QuickSight.
• Learn and grow in both the technical and business-facing sides of data.

Requirements

• 1–3 years of experience in a data-related role (data engineering, analytics engineering, BI) — or strong projects/coursework if you're just starting out.
• Strong experience with SQL and Python for building, manipulating, and analyzing data
• Comfortable with modern data tooling such us - Snowflake, dbt, Airflow, or similar
• Enthusiastic about working collaboratively with teammates and stakeholders to deliver business value from data
• Strong communicator and continuous learner, ready to tackle new challenges in a fast-paced environment
• 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.

Nice to Have:

• Experience with AWS or other cloud platforms.
• Familiarity with streaming data (Kafka), Infrastructure as Code (Terraform), or Git-based workflows
• Knowledge of SaaS analytics, especially for product or customer behavior.
• Understanding of PII, data privacy, or compliance standards.

Why Join Us?

• Have a direct impact on global-scale products by delivering high-quality data and analytics
• Grow your skills across the data stack — engineering, analytics, and beyond.
• Work with smart, friendly teammates who love what they do.
• Enjoy a flexible, autonomous environment that encourages ongoing learning and ownership
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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.