Senior Data Engineer
3 weeks ago
Roles and Responsibilities
➔ Review and analyze existing data collection systems, and make recommendations on improvement, maintenance, or other factors to improve the system
➔ Supervising junior data engineering teams to ensure they carry out their duties in line with the business's goals
➔ Responsible for designing, deploying, and maintaining the organization's data platforms
➔ Identifying opportunities for improving the performance and efficiency of data platforms and implementing enhancements to meet service-level agreements (SLAs)
➔ Collaborating with clients to understand their data-related needs, providing recommendations, and delivering solutions that meet their requirements and expectations.
Skillsets Requirements Technical Skills
➔ Proficient in cloud platforms such as AWS, Azure, or Google Cloud Platform for deploying and managing data solutions in the cloud. Exposure to GCP is preferable.
➔ Strong expertise in building and optimizing ETL processes to efficiently move and transform data between various systems and storage solutions.
➔ Knowledge of data warehousing concepts and experience working with data warehouse solutions like Amazon Redshift, Snowflake, or Google BigQuery.
➔ Extensive understanding of Python and advanced SQL, with the skill to create efficient queries. ➔ Familiarity with big data technologies such as Apache Hadoop, Apache Spark, and related tools for processing and analyzing large volumes of data.
➔ Experience in managing and optimizing relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
➔ Identification, analysis, and resolution of infrastructure vulnerabilities and application deployment issues.
➔ Capable of resolving code errors and finding solutions for any issues in the pipeline.
Soft Skills
➔ Skilled in handling numerous projects simultaneously.
➔ Engage directly with end users to collect requirements and advise on data integration solutions ➔ Leadership qualities to guide and mentor junior team members, contributing to their professional development.
➔ Strong analytical and problem-solving skills to address challenges and troubleshoot issues in data engineering processes.
➔ A meticulous approach to ensure data accuracy, quality, and adherence to best practices in data engineering processes.
➔ Enthusiasm for continuous learning to stay updated on industry trends, emerging technologies, and best practices in data engineering.
➔ Excellent verbal and written communication skills is a must.
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