Senior Data Engineer

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.