The Senior Data Engineer is responsible for overseeing junior data engineering activities and aiding in building the business data collection systems and processing pipelines. The role of the Senior Data Engineer is responsible for building and maintaining optimized and highly available data pipelines that facilitate deeper analysis and reporting by the Data and Analytics department.
The Senior Data Engineer builds data processing frameworks that handle the businesss growing database. He works with senior data science leadership as well as other Data and Analytics teams in leveraging data with reporting and scientific tools, for example, Tableau, R, and Spark. The Senior Data Engineer strives to continuously develop new and improved data engineering capabilities.
Management and Strategy: The managerial role of the Senior Data Engineer is primarily for overseeing activities of the junior data engineering teams, ensuring proper execution of their duties and alignment with business vision and objectives. He provides senior-level contribution to a team that is responsible for the design, deployment, and maintenance of the businesss data platforms.
However, the Senior Data Analyst will also implement strategies directed at acquiring data and promoting the development of new insights across the business. The Senior Data Engineer owns and extends the businesss data pipeline through the collection, storage, processing, and transformation of large data-sets.
It is his duty to monitor the existing metrics, analyze data, and lead partnership with other Data and Analytics teams in an effort to identify and implement system and process improvements.
The Senior Data Engineer will additionally develop queries for ad hoc business projects, as well as ongoing reporting. In this capacity, the Senior Data Engineer builds a metadata system where all available data is maintained and cataloged. The Senior Data Engineer also plays a major role in the development of reliable data pipelines that translate raw data into powerful features and signals.
He designs, architects, implements, and supports key datasets that avail structured and timely access to actionable business insights. The Senior Data Engineer is additionally tasked with developing ETL processes that convert data into formats through a team of data analysts and dashboard charts.
Collaboration and Support: The Senior Data Engineer plays a collaborative role where he works closely with the businesss Data and Analytics teams, gathering technical requirements for exceptional data governance across the department and the business at large.
In this collaboration, the Senior Data Engineer works the data analysts, data warehousing engineers, and data scientists in finding and applying best practices within the Data and Analytics department as well as defining the businesss data requirements, which will ensure that the collected data is of a high quality and optimal for use across the department and the business at large.
The Senior Data Engineer will also work with senior data science management and departments beyond the Data and Analytics department in analyzing and understanding data sources, participating in design, and providing insights and guidance on database technology and data modeling best practices.
In this capacity, the Senior Data Engineer will further be required to draw performance reports and strategic proposals form his gathered knowledge and analyses results for senior data science leadership.
Analytics: The Senior Data Engineering plays an analytical role where he develops and manages scalable data processing platforms that he uses for exploratory data analysis and real-time analytics. It is also the role of the Senior Data Engineer to oversee, design, and develop algorithms for real-time data processing within the business and to create the frameworks that enable quick and efficient data acquisition.
In this capacity, the Senior Data Engineer retrieves and analyzes data through the use of SQL, Excel, among other data management systems. He also builds data loading services for the purpose of importing data from numerous disparate data sources, inclusive of APIs, logs, relational, and non-relational databases.
Knowledge and Opportunity: The Senior Data Engineer is tasked with the responsibility of contributing to the continual improvement of the businesss data platforms through his observations and well-researched knowledge. He keeps track of industry best practices and trends and through his acquired knowledge, takes advantage of process and system improvement opportunities.
The Senior Data Engineer performs similar duties as he deems fit for the proper execution of his duties and duties as delegated by the Head of Data Science, Director Data Science, Chief Data Officer, or the Employer.
Education: The Senior Data Engineer must have a bachelors degree (masters preferred) in Computer Science, Applied Mathematics, Engineering, or any other technology related field. An equivalent of this educational requirement in working experience is also acceptable.
Experience: A candidate for this position must have had at least 5 years of working experience working in a data engineering department, preferably as a Data Engineer in a fast-paced environment and complex business setting. The candidate must have a demonstrated experience in building and maintaining reliable and scalable ETL on big data platforms as well as experience working with varied forms of data infrastructure inclusive of relational databases such as SQL, Hadoop, Spark and column-oriented databases such as Redshift, MySQL, and Vertica.
The candidate must also have had experience in data warehousing inclusive of dimensional modeling concepts and demonstrate proficiency in scripting languages, for example, Python, Perl, and so forth. A suitable candidate will also demonstrate machine learning experience and experience with big data infrastructure inclusive of MapReduce, Hive, HDFS, YARN, HBase, Oozie, etc. The candidate will additionally demonstrate substantial experience and a deep knowledge of data mining techniques, relational, and non-relational databases.
Communication Skills: Communication Skills for the Senior Data Engineer are just as important as they are for the Data Engineer, both in verbal and written form. The Senior Data Engineer oversees and manages junior data engineering teams and to ensure effective management, he must be capable of conveying information and instructions clearly down the line to the junior team.
Communication skills are also imperative for the Senior Data Engineer in his collaborative role where he will have to interact cross-functionally with non-technical departments. To enable effective collaborations, the Senior Data Engineer will have an exceptional ability to convey complex messages in a clear, simplified, and understandable manner.
He will also be required to draft reports and prepare presentations for senior data science leadership. These reports and presentation must be clear, concise, unambiguous, engaging and convincing, which will demand exceptional communication skills on the Senior Data Engineers part.
Skills: A candidate for this position will also demonstrate strong computer skills and a deep passion for analytics. The candidate for this position must possess an ability to perform complex data analyses with large data volumes. He will be an expert in SQL, Java, and have a keen understanding of data models and data warehouse concepts.
The candidate will demonstrate an ability translate algorithms provided by senior data science management and implement them in as well as strong knowledge in Linux, OS tools, and file-system level troubleshooting. The candidate must have substantial experience working with big data infrastructure tools such as Python, SQS, and Redshift. A suitable candidate will also be proficient Scala, Spark, Spark Streaming, AWS, and EMR.
The Senior Data Engineer must have certain preferable personal attributes that will make him that much more suited for the position. The Senior Data Engineer will be a result-driven individual, be passionate and a self-starter, be proactive requiring minimal supervision, be highly organized, have an ability to handle multiple tasks and meet tight deadlines, be a creative and strategic thinker, work comfortably work in a collaborative setting, work comfortably with senior departmental leadership, and demonstrate an ability to remain calm during times of uncertainty and stress, inspiring the same in his team.
The candidate must be a people person who is able to form strong, meaningful, and lasting connections with others, enabling smooth and continued collaborative relationships, earning him the trust of his juniors who will readily follow in his directives, and gaining the confidence of senior data science leadership.
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