

· Maintain optimal data ingestion pipeline architectures. Construct large, complex data sets to meet business requirements.
· Develop and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
· Develop the infrastructure necessary for optimal data extraction, transformation, and loading using SQL and big data technologies.
· Implementing scripts for database maintenance, monitoring, and performance tuning
· Analyze the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business metrics.
· Providing technical support to stakeholders, including executive, product, data, and design teams, regarding data-related issues.
· Develop data tools to assist analytics and data scientist team members in building and optimizing our product into an industry leader.
· Maintain, monitor, and tune the performance of databases using scripts.
· To populate databases and to create aggregates, develop ETL routines.
· Perform data updates, indexing, and maintenance in the application database.
Requirements:
· Big data tools: Apache Hadoop (YARN, and HDFS), Spark, Kafka, etc.
· Relational SQL and NoSQL databases.
· Data pipeline and workflow management tools: Airflow/Luigi, etc.
· Stream-processing systems: Storm/Spark-Streaming, etc.
· Object-Oriented/object function scripting languages: Python, scala, etc.
· Experience building and optimizing data ingestion pipelines.
· Comfortable with working on Linux-operated machines.
· Experience supporting and working with cross-functional teams in a dynamic environment.
· Minimum one year of experience in the field of data engineering
· Master or PhD Degree in electrical engineering/ software engineering/ computer science/ computer engineering/ or related.
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