Senior Data Engineer
Alison Tel-Aviv, Tel-Aviv District, Israel
Software Development · 11-50 employees
About the role
The Senior Data Engineer will architect, develop, and maintain robust end-to-end data pipelines and complex data models to support AI models and business intelligence. They will also ensure platform reliability, optimize data performance, and collaborate cross-functionally to integrate data solutions.
What they look for
Requirements
Candidates must have 7+ years of experience in data engineering with strong proficiency in SQL and programming languages like Python, Scala, or Java. Expertise in distributed data processing, cloud platforms, and software engineering best practices is essential for this role.
Full description
We are seeking talented and passionate Senior Data Engineer to join our Data team. In this pivotal role, you will be instrumental in designing, building, and optimizing the critical data infrastructure that underpins Alison.ai's innovative creative intelligence platform. You will tackle complex data challenges, ensuring our systems are robust, scalable, and capable of delivering high-quality data to power our advanced AI models, customer-facing analytics, and internal business intelligence. This is an opportunity to make a significant impact on our product, contribute to a data-driven culture, and help solve fascinating problems at the intersection of data, AI, and marketing technology.
Key Responsibilities
- Architect & Develop Data Pipelines: Design, implement, and maintain sophisticated, end-to-end data pipelines for ingesting, processing, validating, and transforming large-scale, diverse datasets.
- Manage Data Orchestration: Implement and manage robust workflow orchestration for complex, multi-step data processes, ensuring reliability and visibility.
- Advanced Data Transformation & Modeling: Develop and optimize complex data transformations using advanced SQL and other data manipulation techniques. Contribute to the design and implementation of effective data models for analytical and operational use.
- Ensure Data Quality & Platform Reliability: Establish and improve processes for data quality assurance, monitoring, alerting, and performance optimization across the data platform. Proactively identify and resolve data integrity and pipeline issues.
- Cross-Functional Collaboration: Partner closely with AI engineers, product managers, developers, customer success and other stakeholders to understand data needs, integrate data solutions, and deliver features that provide exceptional value.
- Drive Data Platform Excellence: Contribute to the evolution of our data architecture, champion best practices in data engineering (e.g., DataOps principles), and evaluate emerging technologies to enhance platform capabilities, stability, and cost-effectiveness.
- Foster a Culture of Learning & Impact: Actively share knowledge, contribute to team growth, and maintain a strong focus on how data engineering efforts translate into tangible product and business outcomes.
Requirements
What we are looking for:
- 7+ years of experience as a Data Engineer, building and managing complex data pipelines and data-intensive applications.
- Solid understanding and application of software engineering principles and best practices. Proficiency in a relevant programming language (e.g., Python, Scala, Java) is highly desirable.
- Deep expertise in writing, optimizing, and troubleshooting complex SQL queries for data transformation, aggregation, and analysis in relational and analytical database environments.
- Hands-on experience with distributed data processing systems, cloud-based data platforms, data warehousing concepts, and workflow management tools.
- Strong ability to diagnose complex technical issues, identify root causes, and develop effective, scalable solutions.
- A genuine enthusiasm for tackling new data challenges, exploring innovative technologies, and continually expanding your skillset.
- A keen interest in understanding how data powers product features and drives business value, with a focus on delivering results.
- Excellent ability to communicate technical ideas clearly and work effectively within a multi-disciplinary team environment.
Advantages:
- Familiarity with the marketing/advertising technology domain and associated datasets.
- Experience with data related to creative assets, particularly video or image analysis.
- Understanding of MLOps principles or experience supporting machine learning workflows.
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