Data Engineer

Job Description Roles & Responsibilities Job Title: Data Engineer Job Description: We are seeking a highly skilled and motivated Data Engineer to play a pivotal role in designing, building, and optimizing our next-generation scalable data pipelines. This position requires expertise in processing massive datasets using cutting-edge technologies like Apache Spark, PySpark, and Hive within Cloudera Platform.

Your primary objective will be to ensure the utmost data reliability, speed, and efficiency, providing a robust foundation for downstream business intelligence and advanced analytics initiatives.

Roles & Responsibilities

Data Pipeline Development & Maintenance: Design, build, and maintain highly scalable and efficient ETL/ELT data pipelines utilizing PySpark and Spark SQL , Hive for complex data transformations.

Data Warehousing & Storage Optimization

Strategically manage data layout, partitioning, and indexing within Apache Hive and various cloud data lake solutions to optimize performance and accessibility.

Performance Tuning & Optimization

Proactively identify and resolve performance bottlenecks in Spark jobs, leveraging Spark UI for in-depth analysis, effectively managing data skewness, and optimizing memory utilization.

Diverse Data Integration

Develop robust solutions for ingesting high-volume and diverse datasets from both structured relational databases and unstructured flat files into our data ecosystem.

Automated Workflow Orchestration

Implement and manage automated data workflows using industry-standard scheduling tools like Apache Airflow or platform-native schedulers, ensuring timely and reliable data delivery.

Strategic Collaboration

Partner closely with data scientists, business analysts, and cross-functional enterprise teams to translate complex business requirements into technically sound and efficient data solutions.

Qualifications

Big Data Frameworks Expertise: Demonstrated high proficiency in Apache Spark architecture, including a deep understanding of drivers, executors, and Directed Acyclic Graphs (DAGs).

Advanced Programming

Exceptional coding skills in Python and extensive experience with the PySpark API for developing intricate data transformations and processing logic.

Querying & Schema Management

Strong command of HiveQL and ANSI SQL, coupled with expertise in data partitioning techniques and effective schema definition.

Optimized Storage Formats

In-depth understanding and practical experience with optimized big data storage file formats such as Parquet, ORC, and Avro.

Data Warehousing Fundamentals

Solid foundation in Dimensional Data Modeling, including Star and Snowflake schemas, and practical experience with Data Lakes concepts and implementation.

Preferred Qualifications

CI/CD & DevOps Automation: Experience with Continuous Integration/Continuous Deployment (CI/CD) practices and automation tools like Git, Jenkins, or Ansible.

Cloud Ecosyste m Development

Experience in development experience utilizing cloud-native big data utilities (e.g., AWS EMR, AWS Databricks) within major cloud platforms.

NoSQL Database Integration

Exposure to and experience with NoSQL databases such as HBase, Cassandra, or MongoDB.

Professional Certifications

Relevant professional certifications on Spark or Data Engineer are highly valued Salary Range: $125,000 to $140,000 per year Qualifications: BACHELOR OF COMPUTER SCIENCE