Data Engineering Delivery Manager
United States
Nexient
Nexient is America’s largest 100% US-based software development consulting firm. We help clients outpace their competition through agile development, digital innovation and product-minded / project to product strategies.Delivery Manager (Data engineering) is a highly visible and strategic role in our Data engineering practice.
Roles and Responsibilities:
- Building and maintaining optimized and highly available data pipelines to facilitate deeper analysis and reporting.
- Design and build data processing frameworks that handle the business’s growing database.
- Works with senior data science leadership as well as other Data and Analytics team members in leveraging data with reporting and scientific tools.
- Strives to continuously develop new and improved data engineering capabilities.
- Implement strategies directed at acquiring data and promoting the development of new insights across the business.
- Owns and extends the business’s data pipeline through the collection, storage, processing, and transformation of large data-sets.
- 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.
- Develop complex queries for ad hoc business projects, as well as ongoing reporting.
- Build a metadata system where all available data is maintained and cataloged.
- Play a major role in the development of reliable data pipelines that translate raw data into powerful features and signals.
- Designs, architects, implements, and supports key datasets that avail structured and timely access to actionable business insights.
- Developing ETL processes that convert data into formats through a team of data analysts and dashboard charts.
- Plays a collaborative role where he works closely with the business’s Data and Analytics teams, gathering technical requirements for exceptional data governance across the department and the business at large.
- 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.
- Performance reports and strategic proposals form his gathered knowledge and analyses results for senior data science leadership.
- Plays an analytical role where he develops and manages scalable data processing platforms that he uses for exploratory data analysis and real-time analytics.
- 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.
- Retrieves and analyzes data through the use of SQL, Excel, among other data management systems.
- Build data loading services for the purpose of importing data from numerous disparate data sources, inclusive of APIs, logs, relational, and non-relational databases.
- Responsibility of contributing to the continual improvement of the business’s data platforms through his observations and well-researched knowledge.
Qualifications:
- Bachelor’s 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.
- A candidate for this position must have had at least 8 years of working experience working in a data engineering in a fast-paced environment and complex business setting.
- 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.
- Strong SQL application development skills
- Strong experience with SQL Server, Excel, Tableau, PowerBI, Microsoft SQL Reporting Service (SSRS), scripting languages
- 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.
- 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.
- Oversee and manage 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 imperative in this collaborative role where he will have to interact cross-functionally with non-technical departments.
- Effective collaborations, with an exceptional ability to convey complex messages in a clear, simplified, and understandable manner.
- 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
- Exceptional skills in SQL server reporting services, analysis services, Tableau, Salesforce, integration services, or any other data visualization tools.
- Must possess an ability to perform complex data analyses with large data volumes.
- Expert in SQL and have a keen understanding of data models and data warehouse concepts.
- 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.
- 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.
- 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile ANN APIs AWS Big Data Computer Science Data analysis Data management Data Mining Data pipelines Data visualization Data Warehousing EDA Engineering ETL Excel Hadoop HBase HDFS Machine Learning Mathematics MySQL Oozie Perl Pipelines Power BI Python RDBMS Redshift Scala Spark SQL Streaming Tableau UX
Perks/benefits: Career development Flex hours Flexible spending account Flex vacation Health care Insurance Medical leave
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