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As a Senior Engineer specializing in Databricks, you will be instrumental in designing and implementing scalable data engineering solutions.

Key responsibilities include: - Developing data ingestion, transformation, and processing architectures that align with business needs. - Architecting and optimizing solutions using Snowflake or Delta Lake on Databricks for enterprise-scale data platforms. - Leading the implementation of high-performance batch and streaming data pipelines. - Designing event-driven data architectures utilizing Apache Kafka or Amazon Kinesis. - Establishing robust monitoring, scheduling, and operational controls for reliable pipeline execution. - Driving data quality, validation, reconciliation, and governance practices. - Promoting the responsible use of AI-assisted engineering to enhance development productivity and solution quality. - Mentoring team members on PySpark, Snowflake, Delta Lake, Kafka, Kinesis, Airflow, and data engineering best practices. - Collaborating with cross-functional teams to ensure seamless end-to-end data platform delivery.

We are seeking a Senior Engineer with 7-8 years of experience in data engineering.

Mandatory skills include: - Databricks Workflows - Apache Spark - Data Quality & Validation - PySpark - SQL - Apache Kafka - Snowflake

Additional expertise in Azure Databricks is a plus.

Ideal candidates demonstrate strong ownership, collaborate effectively with stakeholders, and possess a quality-focused engineering mindset. You should apply strong analytical thinking to complex challenges, adapt to evolving technologies, and communicate delivery status, risks, and dependencies clearly. A high attention to detail across architecture, design, testing, and implementation is essential.