Data Engineering Team Lead at Flare

Tel-Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

10 Oct, 26

Salary

0.0

Posted On

12 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Team Leadership, SQL, Python, Kafka, ClickHouse, Flink, Airflow, dbt, Snowflake, PostgreSQL, Data Architecture, AI/ML Pipelines, Data Modeling, Infrastructure-as-Code, Data Governance

Industry

Software Development

Description

About Us Hello, we’re Flare! We are reimagining how attorneys and clients work together. We are obsessed with building solutions that empower attorneys and consumers through the legal journey. Funded by leading VC firms, we are an industry leader in legal technology. Our platform simplifies the delivery of complex legal services while providing ease and clarity to clients and attorneys throughout the process. With a global team that brings a fresh perspective, Flare is revolutionizing the way legal services are delivered. We’re a team of creative problem-solvers who want to make the world a better place. Join us. Overview At Flare, reliable and scalable data infrastructure isn’t just a technical goal - it’s central to our ability to power AI-driven innovation and enrich our product offerings. As Data Engineering Team Lead, you’ll combine hands-on technical expertise with people-first leadership. You’ll own the strategy, architecture, and delivery of our production data layer and guide a growing team of data engineers to build the foundations that enable data-powered product development across the company. What You’ll Do Set Vision & Roadmap: Define the data engineering strategy in partnership with product, AI, and platform leads. Stay Hands-On: Lead critical design reviews and own complex components (~80% coding), troubleshooting as needed. Lead & Grow Team: Manage, hire, and mentor a high-performing team, driving career growth and accountability. Own the Data Platform: Build and scale real-time and batch infrastructure with strong SLAs and compliance. Ensure Quality: Establish standards for modeling, observability, orchestration, and governance. Collaborate Cross-Functionally: Partner with backend, platform, AI/ML, and product teams to deliver data-powered features. Champion Excellence: Promote data best practices and foster a culture of ownership and improvement. Requirements 7+ years of professional experience in data engineering, with 2+ years leading or managing engineers. Proven track record of building and operating production-grade data platforms (streaming and batch) using technologies such as Kafka, ClickHouse, Flink, Airflow, dbt, Snowflake, PostgreSQL,or equivalents. Advanced proficiency in SQL and Python. Demonstrated ability to set technical direction, prioritize roadmaps, and deliver results through others. Strong understanding of data architecture, reliability, scalability, and best practices for AI/ML pipelines. Excellent communication and collaboration skills; comfortable influencing senior stakeholders and working cross-functionally. Bachelor’s or Master’s degree in Computer Science, Information Systems, or equivalent experience. Bonus Points Experience transitioning from monolithic data platforms to Data Mesh or decentralized data ownership models. Background in implementing data governance frameworks or compliance (e.g., GDPR, CCPA). Prior success leading teams that built platforms supporting AI/ML workloads end-to-end. Familiarity with infrastructure-as-code (e.g., Terraform) and cloud-native data services (AWS, GCP, or Azure). Flare provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Responsibilities

Lead the strategy, architecture, and delivery of the production data layer while managing and mentoring a team of data engineers. Balance people leadership with hands-on technical work, owning approximately 80% of coding for complex components.