Lead I - Software Engineering _ Data Engineer

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,