Senior Data Architect

3 weeks ago

Irving, Texas, United States Anblicks Full time

Data Engineering Solutions Developer

The ideal candidate will be responsible for designing and developing data engineering solutions using next-generation data techniques. This role will involve working closely with product owners, customers, and technologists to deliver data products and solutions in a collaborative and agile environment.

Key Responsibilities:

  • Design and develop big data solutions using Hadoop and other big data technologies.
  • Partner with domain experts, product managers, analysts, and data scientists to develop big data pipelines.
  • Responsible for moving legacy workloads to cloud platforms.
  • Work with data scientists to build client pipelines using heterogeneous sources and provide engineering services for data science applications.
  • Ensure automation through CI/CD across platforms in cloud and on-premises environments.
  • Define needs around maintainability, testability, performance, security, quality, and usability for data platforms.
  • Drive implementation, consistent patterns, reusable components, and coding standards for data engineering processes.
  • Convert SAS-based pipelines into languages like PySpark, Scala, and execute on Hadoop and non-Hadoop ecosystems.
  • Tune big data applications on Hadoop and non-Hadoop platforms for optimal performance.
  • Evaluate new IT developments and evolving business requirements and recommend appropriate systems alternatives and/or enhancements to current systems.

Qualifications:

  • 8+ years of total IT experience.
  • 5+ years of experience with Hadoop (Cloudera)/big data technologies.
  • Advanced knowledge of the Hadoop ecosystem and big data technologies.
  • Hands-on experience with the Hadoop ecosystem (HDFS, MapReduce, Hive, Pig, Impala, Spark, Kafka, Kudu, Solr).
  • Experience designing and developing data pipelines for data ingestion or transformation using Java, Scala, or Python.
  • Experience with Spark programming (PySpark, Scala, Java).
  • Expert-level building pipelines using Apache Spark.
  • Familiarity with core provider services from AWS, Azure, or GCP, preferably having supported deployments on one or more of these platforms.
  • Hands-on experience with Python, PySpark, Scala, and basic libraries for machine learning.
  • Exposure to containerization and related technologies (e.g., Docker, Kubernetes).
  • Exposure to aspects of DevOps (source control, continuous integration, deployments, etc.).
  • Proficient in programming in Java or Python with prior Apache Beam/Spark experience a plus.
  • System-level understanding - data structures, algorithms, distributed storage & compute.
  • Can-do attitude on solving complex business problems, good interpersonal and teamwork skills.
  • Possess team management experience and have led a team of data engineers and analysts.
  • Experience in Snowflake is a plus.

Education:

  • Bachelor's degree/University degree or equivalent experience.

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