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Big Data Engineer

  • Location: Philadelphia, 19130
  • Salary: 92.89
  • Job Type:Contract

Posted 7 days ago

Work with the brightest minds at one of the largest financial institutions in the world. This is long-term contract opportunity that includes a competitive benefit package!

Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.

Position: Big Data Engineer
Location: PHILADELPHIA, Pennsylvania, 19130
Term: 12 months

Day-to-Day Responsibilities:

  • Lead complex initiatives on selected domains.
  • Ensure systems are monitored to increase operational efficiency and managed to mitigate risk.
  • Define opportunities to maximize resource utilization and improve processes while reducing cost.
  • Lead, design, develop, test and implement applications and system components, tools and utilities, models, simulation, and analytics to manage complex business functions using sophisticated technologies.
  • Resolve coding, testing and escalated platform issues of a technically challenging nature.
  • Lead team to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives.
  • Mentor less experienced software engineers.
  • Collaborate and influence all levels of professionals including managers.
  • Lead team to achieve objectives.
  • Partner with production support and platform engineering teams effectively.


Is this a good fit? (Requirements):

  • 7+ years of Big Data Platform (data lake) and data warehouse engineering.
  • Very strong Python and other functional programming skills.
  • 5+ years of experience with Hadoop stack: HDFS, Hive, SQL, Spark, Spark Streaming, Spark SQL, HBase, Kafka, Sqoop, Atlas, Flink, Kafka, Cloudera Manager, Airflow, Impala, Hive, HBase, Tez, Hue, and a variety of source data connectors.
  • Hands-on experience designing and building microservices, APIs and, MySQL.
  • Hands-on experience with building modern, resilient, and secure data pipelines, including movement, collection, integration, transformation of structured/unstructured data with built-in automated data controls, and built-in logging/monitoring/alerting, and pipeline orchestration managed to operational SLAs.
  • Hands-on experience developing and managing technical and business metadata.
  • Hands-on experience creating/managing Time-Series data from full data snapshots or incremental data changes.
  • Hands-on experience with implementing fine-grained access controls such as Attribute Based Access Controls using Apache Ranger.
  • Experience automating DQ validation in the data pipelines.
  • Experience implementing automated data change management including code and schema, versioning, QA, CI/CD, rollback processing.
  • Experience with automating end to end data lifecycle on the big data ecosystem.
  • Experience with managing automated schema evolution within data pipelines.
  • Experience with implementing masking and/or other forms of obfuscating data.
  • Experience automating data pipelines to leverage static and operational metadata.
  • Experience developing automated solutions for Data Registration and Classification of technical metadata.
  • Advanced understanding of SQL and NoSQL DB schemas.
  • Advanced understanding of Partitioned Parquet, ORC, Avro, various compression formats.
  • Experience with any one of Ansible, Chef, Puppet, Python, Linux Scripts.
  • Development of automation around DevOps style data pipeline deployments and rollbacks.
  • Developing containerized Microservices and APIs.
  • Understanding of Data Governance policies and standards.
  • Google cloud data services experience (bonus).
  • Familiarity with key concepts implemented by Apache Hudi or Iceberg, or Databricks Delta Lake.
  • 5+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.