Data Engineer

The Vulnerability Management Platforms Development Squad is seeking a highly skilled Data Engineer with deep expertise in PostgreSQL, Snowflake, or ElasticSearch. The ideal candidate will possess advanced experience in data modeling, ETL processes, and building large-scale data solutions. A strong technical background in data engineering, as well as expertise in streaming services (e.g., Kafka), is required for this role.

Key Responsibilities:

• Data Pipeline Development: Build, optimize, and manage data pipelines, orchestration tools, and governance frameworks to ensure efficient, high-quality data flow.
• Data Quality & Governance: Perform data quality checks, enforce governance standards, and apply quality rules to ensure data integrity.
• Real-time Data Processing: Utilize Python and streaming technologies (e.g., Kafka) for real-time data processing and analytics, with PostgreSQL as the source.
• Advanced SQL Development: Write complex SQL queries for data manipulation, analysis, and integration.
• Snowflake or ElasticSearch Architecture & Implementation: Design and implement large-scale data integration solutions using Snowflake or ElasticSearch.

Required Qualifications:

• Experience: 8+ years in IT with a focus on data engineering and architecture.
• Technical Expertise: In-depth knowledge of PostgreSQL, with additional expertise in Snowflake or ElasticSearch. Proficient in architecture, functions, and data warehousing concepts for both platforms.
• ETL & Data Modeling: Advanced skills in ETL processes, data modeling, and data warehousing.
• Programming: Proficiency in Python for data engineering tasks.
• Streaming Services: Experience with Kafka or similar real-time data streaming services.
• Communication: Strong analytical, architectural design, and communication skills for engaging with diverse technical stakeholders.

Preferred Qualifications:

• Experience in designing and implementing large-scale data integration solutions.
• Expertise in high-performance data engineering solutions across various cloud platforms.
• Familiarity with other big data tools and technologies is a plus.

Certifications (if any):

Relevant certifications in Data Engineering, Cloud, or Big Data technologies (e.g., Snowflake, Kafka) are a plus but not required