Accolite
Data Engineer
Job Description
Responsibilities:
Build and maintain complex scalable ETL pipelines, ELT/ETL processes from a wide variety of data sources using best practices.
Implement internal process improvements, automate manual processes, data monitoring, and ensure data reliability, efficiency, and quality.
Collaborate closely with business stakeholders such as marketing, product analytics, and data scientists to bridge business requirements with data engineering.
Deploy data pipelines into production based on Continuous Delivery practices and work with technology teams to ensure data remains accessible and relevant.
Requirements:
Bachelor's or Master's degree in Electrical, Electronic, Mechanical Engineering or equivalent.
Experience querying databases using statistical computer languages such as R, Python, and SQL.
Strong expertise in SQL design, implementation, and supporting databases for Business Intelligence.
Hands-on experience with Oracle/MySQL, Airflow, Spark, AWS Cloud (EMR, S3, SNS, SQS), and S3 data lake.
Familiarity with multi-cloud computing platforms like GCP, AWS, Azure, and advanced experience using SQL/NoSQL databases.
Proficiency in web service standards (REST, GraphQL, SOAP) and Git automation tools (Jenkins, Airflow).
Experience with data lake, AWS DMS/DBT, Spark, Postgres SQL, and AWS Redshift databases.
Ability to work with Unix-like operating systems, shell commands, and promote Kubernetes and AWS platform design quality.
Skills:
Strong communication and client-facing skills with the ability to work in a consulting environment.
Proficient in Python, SQL, Java, and other programming languages for building and optimizing data solutions.
Experience working in a cloud environment, preferably AWS, for development, production, and operationalization.
Knowledge of data architecture, Snowflake data warehouse,
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