
Data Architect
22 hours ago
Key Responsibilities:
Design and implement large-scale data pipelines using modern big data technologies.
Build scalable and efficient distributed data processing systems using Hadoop, Spark, Hive, and Kafka.
Work extensively with cloud platforms (AWS) and services like EMR, Glue, Lambda, Athena, S3.
Design and implement data integration solutions pulling from multiple sources into a centralized data warehouse or data lake.
Develop pipelines using DBT and manage workflows with Apache Airflow or Step Functions.
Write clean, maintainable, and efficient code using Python, PySpark, or Scala for data transformation and processing.
Build and manage relational and columnar data stores such as PostgreSQL, MySQL, Redshift, Snowflake, HBase, ClickHouse.
Implement CI/CD pipelines using Docker, Jenkins, and other DevOps tools.
Collaborate with data scientists, analysts, and other engineering teams to deploy data models into production.
Drive data quality, integrity, and consistency across systems.
Participate in Agile/Scrum ceremonies and utilize JIRA for task management.
Provide mentorship and technical guidance to junior team members.
Contribute to continuous improvement by making recommendations to enhance data engineering processes and architecture.
5+ years of hands-on experience as a Data Engineer.
Deep knowledge of Big Data technologies – Hadoop, Spark, Hive, Kafka.
Expertise in Python, PySpark and/or Scala.
Proficient with data modeling, SQL scripting, and working with large-scale datasets.
Experience with distributed storage like HDFS and cloud storage (e.g., AWS S3).
Hands-on with data orchestration tools like Apache Airflow or StepFunction.
Experience working in AWS environments with services such as EMR, Glue, Lambda, Athena.
Familiarity with data warehousing concepts and experience with tools like Redshift, Snowflake.
Exposure to tools like Informatica, AbInitio, Apache Iceberg is a plus.
Knowledge of Docker, Jenkins, and other CI/CD tools.
Strong problem-solving skills, initiative, and a continuous learning mindset.
Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
Experience with open table formats such as Apache Iceberg.
Hands-on with AbInitio (GDE, Collect > IT) or Informatica tools.
Knowledge of Agile methodology, working experience in JIRA.
Self-driven, proactive, and a strong team player.
Excellent communication and interpersonal skills.
Passion for data and technology innovation.
Ability to work independently and manage multiple priorities in a fast-paced environment.
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