Lead I - Software Engineering

Role Description We are seeking a Data Engineer with Spark and Streaming skills builds real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (GCP) to ingest, transform, and deliver data for analytics and ML.

Responsibilities Design, develop, and maintain ETL/ELT data pipelines for batch and real-time data ingestion, transformation, and loading using Spark (PySpark/Scala) and streaming technologies (Kafka, Flink). Build and optimize scalable data architectures, including data lakes, data warehouses (BigQuery), and streaming platforms. Performance Tuning: Optimize Spark jobs, SQL queries, and data processing workflows for speed, efficiency, and cost-effectiveness Data Quality: Implement data quality checks, monitoring, and ing systems to ensure data accuracy and consistency.

Required Skills & Qualifications Programming: Strong proficiency in Python, SQL, and potentially Scala/Java Big Data: Expertise in Apache Spark (Spark SQL, DataFrames, Streaming). Streaming: Experience with messaging queues like Apache Kafka, or Pub/Sub. Cloud: Familiarity with GCP, Azure data services. Databases: Knowledge of data warehousing (Snowflake, Redshift) and NoSQL databases. Tools: Experience with Airflow, Databricks, Docker, Kubernetes is a plus.

Experience Level Total IT Experience – Minimum 8 years GCP - 4 + years of recent GCP experience

Skills big data,spark,bigquery,sql,apache kafka,scala,