Marketing Data Team Lead at Datarails

Tel-Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

02 May, 26

Salary

0.0

Posted On

01 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, Data Engineering, Team Leadership, SQL, Python, ETL, Data Warehousing, Data Visualization, Marketing Analytics, SaaS Metrics, Data Governance, Forecasting, A/B Testing, Performance Measurement, Data Quality, Collaboration

Industry

Software Development

Description

Datarails is a financial planning and analysis platform that automates financial reporting and planning while enabling finance teams to continue using Excel’s familiar spreadsheets and financial models. We are seeking an experienced Data Team Lead to build, lead, and scale our data function. This is a hands-on leadership role that combines strategic thinking, technical excellence, and people management. You will build and manage a team of Data Engineers and Data Analysts, while working closely with senior management and cross-functional leaders to translate data into measurable business impact. This role is ideal for someone who thrives in a fast-paced startup environment, enjoys influencing decision-making at the highest levels, and is passionate about embedding a data-driven mindset across the organization. About The Role null What You'll Do Lead and mentor the Data team, and support their professional growth while achieving impact goals of the marketing data structure such as: multi touch attribution model, creative analytics and automated data governance processes. Define and own the data vision, roadmap, infrastructure, and best practices aligned with company objectives. Act as a trusted data partner to executive leadership and senior stakeholders, influencing strategy through insights and analysis while promoting a strong data-driven culture. Oversee the design, build, and maintenance of a scalable and reliable data warehouse. Lead the design, implementation, and optimization of ETL/ELT pipelines to integrate data from multiple internal and external sources. Ensure high standards for data quality, governance, integrity, and documentation. Translate complex datasets into clear, actionable insights that support the different departments' needs and the company growth through operational excellence. Support advanced analytics use cases including forecasting, experimentation (A/B testing), and performance measurement. Review and elevate dashboards, reports, and analyses to ensure clarity, accuracy, and executive relevance. Identify gaps in data collection and proactively propose solutions to improve visibility and decision-making. Requirements Experience & Background Bachelor’s or Master’s degree in Analytics, Statistics, Mathematics, Data Science, Computer Science, or a related field - Preferred 5+ years of experience in data analytics or data engineering leadership roles, preferably in a SaaS or technology-driven environment. Experience building data infrastructure, standards, and best practices from the ground up. Previous experience leading projects and mentoring or managing team members - a must. High attention to detail and commitment to data accuracy and quality. Proactive, collaborative, and comfortable operating in a fast-growing startup environment. Technical Skills Strong proficiency in SQL and Python for data manipulation and analysis. Hands-on experience with ETL tools and frameworks (e.g., Apache Airflow, dbt or similar). Solid understanding of data warehousing concepts and platforms (e.g., Snowflake, Redshift, BigQuery). Experience with data visualization tools such as Tableau, Power BI, or Looker. Familiarity with marketing and product analytics tools: user acquisition ad managers APIs, Salesforce and HubSpot data and integrations. Strong understanding of SaaS metrics including ARR, churn, LTV, CAC, and cohort analysis. What We Need null What We Offer null EEO Statement null

Responsibilities

Lead and mentor the Data team while achieving impact goals related to marketing data structures. Oversee the design and maintenance of a scalable data warehouse and ensure high standards for data quality and governance.