Senior Data Engineer (Pyspark, Hadoop, Scala, Hive)- Assistant Vice President

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Job Overview

Senior Data Engineer

We are seeking a highly skilled and motivated Senior Data Engineer to design, develop, and implement cutting-edge data engineering solutions using modern big data and cloud technologies. In this role, you will collaborate with product owners, data scientists, analysts, and technologists to deliver scalable, high-performance data products in an agile and collaborative environment. You will also play a key role in migrating legacy workloads to the cloud, optimizing data pipelines, and mentoring team members on best practices in data engineering.

Key Responsibilities

• Design and develop scalable big data solutions using platforms like Hadoop, Snowflake, or other modern data ecosystems.
• Collaborate with domain experts, product managers, analysts, and data scientists to build robust and efficient data pipelines.
• Lead the migration of legacy workloads to cloud platforms (AWS, Azure, or GCP) while ensuring seamless integration and optimization.
• Develop and implement cloud-native solutions for data processing and storage.
• Partner with data scientists to build data pipelines from heterogeneous sources and provide engineering support for data science applications.
• Enable advanced analytics and machine learning workflows by delivering high-quality data pipelines.
• Implement CI/CD pipelines to automate data engineering workflows across cloud and on-premises platforms.
• Drive automation to improve efficiency and reduce manual intervention in data processes.
• Research and evaluate open-source technologies and recommend their integration into the data platform to enhance functionality and scalability.
• Act as a technical expert and mentor team members on big data and cloud technologies.
• Define and enforce coding standards, reusable components, and consistent patterns for data engineering processes.
• Convert SAS-based pipelines into modern frameworks like PySpark, Scala, or Java for execution on Hadoop and non-Hadoop ecosystems.
• Optimize big data applications for performance and scalability across platforms.
• Analyze evolving business requirements and recommend enhancements or alternatives to current systems.
• Evaluate new IT developments and industry standards to ensure the data platform remains cutting-edge.
• Foster a collaborative and high-performing team environment.
• Ensure compliance with applicable laws, regulations, and organizational policies.
• Apply sound ethical judgment and escalate control issues transparently.

Qualifications

• 8+ years of experience with Hadoop (Cloudera) and big data technologies.
• Advanced knowledge of the Hadoop ecosystem, including HDFS, MapReduce, Hive, Pig, Impala, Spark, Kafka, Kudu, and Solr.
• Proficiency in Java, Python, or Scala.
• Hands-on experience with Spark programming (PySpark, Scala, or Java).
• Familiarity with Apache Beam is a plus.
• Experience with cloud platforms like AWS, Azure, or GCP.
• Proven ability to deploy and manage data solutions on cloud platforms.
• Expertise in designing and developing data pipelines for ingestion, transformation, and processing.
• Experience with Snowflake or Delta Lake is a strong advantage.
• Hands-on experience with containerization tools like Docker and Kubernetes.

• Proficiency in DevOps practices, including source control, CI/CD, and automated deployments.
• Experience with Python libraries for machine learning and data science workflows.
• Strong knowledge of data structures, algorithms, distributed storage, and compute systems.
• 1+ year of SAS experience preferred.
• 1+ year of Hadoop administration experience preferred.

• Strong problem-solving and analytical skills.
• Excellent interpersonal and teamwork abilities.
• Proven leadership experience, including mentoring and managing a team of data engineers and analysts.
• A proactive, "can-do" attitude for solving complex business problems.

Education

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).

This revised job description is concise, well-structured, and highlights the key responsibilities, qualifications, and benefits of the role. It is tailored to attract experienced data engineers with expertise in big data, cloud platforms, and leadership.