Senior/Lead Data Engineer [Scala]

We are seeking a highly skilled and experienced Senior/Lead Data Engineer with expertise in Scala to lead the design, development, and scaling of our data engineering initiatives. This role focuses on building and maintaining robust data pipelines, ensuring seamless integration of commerce purchase and catalog data from numerous sources into our data lake, and driving innovation in data engineering solutions. Responsibilities Architect and maintain scalable ETL/ELT pipelines for batch, micro-batch, and streaming data processing systems Build frameworks for optimal extraction, transformation, and delivery of data using technologies like ADF, Spark, and Kafka Identify and implement process improvements, automating workflows and optimizing data infrastructure for efficiency and scalability Design and implement innovative data service solutions leveraging Spring Boot, ReactJS, or other UI and API-related technologies Ensure governance and adherence to delivery management processes for seamless operations Act as a single point of responsibility for all delivery-related concerns, including client escalations, contractual changes, and team resource management Provide technical leadership, ensuring solutions align with high-quality standards and future-proof architecture planning Write user stories and acceptance criteria for agile and scrum workflows Collaborate with cross-functional teams and stakeholders to align goals and execution Ensure compliance with delivery methodologies and industry best practices, particularly agile approaches Strategically manage delivery risks to maintain smooth project execution Optimize and measure team productivity and throughput for effective delivery Mentor and consult Data Engineering team members to ensure timely and quality deliverables Handle production support and deployment activities in a proactive manner Requirements 3+ years of experience in a data engineering role Proficiency in Scala, Scala 2, and Scala core Expertise in Apache Spark, Databricks, and SQL for designing and scaling data solutions Familiarity with data-related tools and services such as ADF and Kafka, including their integration with data pipelines Strong English communication skills (B1+ or higher) for direct client interaction Nice to have Skills in Spark Streaming and PySpark for advanced data processing scenarios Background in Python for scripting and automation Competency in Apache Kafka and Kafka Streams for real-time data streaming Understanding of Azure cloud infrastructure and services