Data Engineer

V-Soft Consulting Inc.

Malvern, PA, United States

2 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.careerbuilder.com

Tech stack

Artificial Intelligence Airflow Amazon Web Services Amazon S3 Apache HTTP Server Information Systems Computer Programming Databases Continuous Delivery Continuous Integration Data as a Services Extract Transform Load (ETL)

+22 more

Data Mining Data Warehousing Distributed Computing Environment Github Python (Programming Language) Scrum Methodology Cloud Services Data Streaming Enterprise Data Management Jupyter Notebook Scripting Apache Spark Reliability of Systems Cloudformation Data Lakes Pyspark Information Technology AWS Glue Apache Kafka Terraform Data Pipelines Databricks

Job description

· Core Competencies: Python, Apache Spark (PySpark), AWS Glue ETL, Data Lake concepts (Medallion Architecture), Databricks, Sagemaker.

· Infrastructure: CloudFormation/Terraform, CI/CD with GitHub Actions.

· Core Responsibilities: Orchestrate data extraction from diverse legacy and modern sources, engineer high-performance scalable pipelines, and provide expert-level production support to ensure system reliability.

Requirements

Database Extract Transform and Load (ETL), Apache Spark, Amazon Web Services (AWS), Data Lake, Python Programming/Scripting Language, GitHub, Continuous Integration, Continuous Deployment/Delivery, Systems Reliability, Production Support, · Bachelor’s degree in Computer Science or related field.

· Strong hands-on experience with Apache Spark and Glue.

· Proven ability to work with Python-based data pipelines.

· Experience with Git and GitHub Actions is mandatory., · Bachelor’s degree in Computer Science, Engineering, Information

Systems, or related discipline.

· 5-7+ years of enterprise Data Engineering experience.

· Strong Python development experience.

· Advanced SQL programming skills.

· Extensive experience with Apache Spark and PySpark.

· Strong experience with Databricks application.

· Hands-on experience with AWS data services including:

o S3

o AWS Glue, · Experience building enterprise ETL and ELT pipelines.

· Experience in EMR-based Query Cluster workloads, that includes Jupyter notebooks, Park Application and ETL Pipelines.

· Strong understanding of distributed data processing.

· Experience working with large-scale cloud data platforms.

· Strong knowledge of dimensional data modeling.

· Experience implementing CI/CD pipelines.

· Familiarity with Agile/Scrum methodologies.

· Excellent communication and stakeholder management skills., · Financial Services or Asset Management industry experience.

· Knowledge of Apache Iceberg, Delta Lake, or Hudi.

· Experience with Airflow.

· Knowledge of Kafka or Kinesis streaming.

· Experience supporting AI/ML and advanced analytics platforms.

· AWS Professional or Specialty Certifications.

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