דרושים » ניהול ביניים » דרוש /ה Senior data engineer עבור חברת הייטק בשלב מוקדם

Requirements:
Requirements: must have requirements: • Bachelor’s degree in Computer Science, Data Science, Statistics, or another relevant field, or equivalent professional experience. • At least 5 years of experience in Data Engineering, with a focus on Analytics and BI. • Expert-level SQL skills. • Deep experience with PostgreSQL, including performance tuning and optimization. • At least 3 years of experience with Python for data processing, automation, and testing. • At least 3 years of experience designing and implementing large-scale data models. • Experience leading performance optimization in complex data systems. • Experience establishing and implementing Data Governance and Data Quality processes. • Proven ability to translate business requirements into data architecture and technological solutions. • Experience providing technical leadership, mentoring, and leading technological initiatives. • Experience building Data and Analytics platforms from scratch. • Proven experience integrating AI and LLM tools into development and data engineering processes. Advantages: • Experience in FinTech or financial organizations. • Deep familiarity with regulation, information security, and compliance requirements. • Experience working with Data Lakes and Data Warehouses. • Experience with orchestration tools and ELT / ETL processes. • Experience working in cloud environments such as AWS, GCP, or Azure. • Familiarity with streaming technologies and real-time data processing. • Experience leading technology teams or professional excellence groups. Personality requirements: • Fast learning ability and curiosity for new technologies and methodologies. • Strategic thinking and broad system-wide perspective. • Ability to lead and influence without formal authority. • Ability to work independently and manage multiple tasks simultaneously. • High personal responsibility and ability to receive professional feedback. • Initiative, creativity, and ability to solve complex problems. • High motivation and constant drive for excellence. • Excellent interpersonal communication skills and ability to work with multiple stakeholders. • Ability to driv

Requirements:
5+ years of experience in data product management, or as a technical product manager in a big data environment.
Hands-on experience with large-scale data collection, classification, curation, and delivery systems, especially in companies that build or sell data products.
Proven track record in leading cross-functional data initiatives involving data engineering, data science, and analytics teams.
Entrepreneurial mindset- proactive, and effective in ambiguity, moving quickly from insight to execution.
Comfortable in technical, data-heavy environments: collaborate on APIs, pipelines, data quality, and edge cases.
AI fluency: understand how to embed AI into products and internal workflows (from prototyping through production evaluation).
Excellent communication and stakeholder alignment across product, sales, and marketing.
Strong data-driven judgment: define metrics, analyze product/customer data, run experiments, and make clear tradeoffs.
High learning agility, adaptable in a fast-changing data and AI landscape.

Requirements:
Strong hands-on experience with applied AI, data engineering, data analysis, product analytics, or machine learning (Must).
Strong coding skills, especially Python and SQL (Must).
Experience with data platforms and analytics tools such as Snowflake, Elasticsearch, Databricks, or Mixpanel.
Proven ability to build AI prototypes, data pipelines, dashboards, monitoring flows, alerts, and KPI infrastructure.
Strong cybersecurity background, from either military service or a cybersecurity company.
Strong analytical thinking, with the ability to turn raw data into clear insights, product opportunities, and AI ideas.
Strong communication skills and the ability to work with both technical and business stakeholders.
Bachelor's degree in Information Systems, Computer Science, Data Science, Engineering, or a related field.

Requirements:
10+ years of experience in Data, Analytics, Cloud, or Enterprise Technology.
At least 5 years of hands-on experience with Databricks.
Strong expertise in modern Data & AI platforms, including Databricks, Spark, SQL, Lakehouse architectures, and cloud technologies (Azure, AWS, or GCP).
Proven experience leading enterprise-scale technology initiatives and managing multidisciplinary teams.
Strong leadership and team-building capabilities, with a track record of developing high-performing professionals.
Excellent presentation, communication, and stakeholder management skills, including engagement with C-level executives.
Strong business acumen with the ability to translate technology capabilities into business value and growth opportunities.