Senior Data Engineer

Our client is seeking a talented Senior Data Engineer to lead a highly complex Data Centric system development. Ideal candidate must have prior experience working with data centric applications and business reporting while working with large and complex datasets. Candidate will be responsible to design, develop and maintain a data analytical platform that will require data cleansing and developing a complex business intelligence model using data visualization and predictive modeling techniques.

The ideal candidate will have strong experience working closely with business and technical teams to design and develop tools and processes to collect, analyze and process large volumes of raw data. The Data Analyst will also be responsible for monitoring and analyzing data accuracy, automate data collection and processing, data modeling, building data visualization tools, dashboards, and reports. The ideal candidate must conduct thorough business requirements analysis to understand and develop technical models to provide sustainable and scalable solutions to meet business needs. Furthermore, the Data Analyst should have strong communication and organizational skills, attention to detail, problem-solving skills. Candidate should have deep technical and analytical skills to break down complex business requirements and provide solutions with high visibility and impact for the business. The candidate should also be able to work on multiple projects at the same time and handle multiple timelines.

Requirements

Primary Responsibilities

Design, implement, and maintain scalable and efficient data pipelines, data warehouses, and ETL processes.

Integrate data from multiple sources, including multiple databases, real-time data, third party data, etc.

Perform data cleansing, preprocessing and transformation of data into data models and ready for data analytics and reporting.

Optimize ETL processes and manage data flows, queries for performance, scalability and reliability.

Develop and maintain data models that fit into business need, ensuring accuracy and integrity.

Utilize industrial tools to perform data analytics and business reports.

Develop and refine predictive models that can be used to make informed decisions.

Able to work with machine learning algorithms to analyze data is a plus.

Create and maintain comprehensive documentation for data flows, data processes and data models.

Collaborate across multiple development teams, business agencies and programs to gather data and business needs.

Stay up to date with industry trends and best practices in data engineering, propose and apply them to improve our data infrastructure.

Must be able to collect, store and associate different data model from different data sources.

Process data, including data cleansing and transformation, in preparation for data analysis.

Use statistical methods and data visualization tools to analyze data, identify trends and patterns.

Create reports, graphs and other visualizations to present and explain data to business.

Working with business and technical members to ensure data is collected accurately and up to date.

Identify business data collection and analysis area of improvement or suggesting changes to current business processes.

Recommend new tools or technologies that can help streamline data analysis.

Able to develop and refine predictive models that can be used to make informed decisions.

Able to work with machine learning algorithms to analyze data is a plus.

Work with business users and technical teams to research, understand, and document technical specifications using common tools such as JIRA, VISIO, SharePoint, MS Office Suite.

Ability to work independently as well as part of a data team in fast paced and dynamic environment.

Qualifications

BS/MS in Computer Science, Data Engineer, Mathematics, Statistics or related field. Master degree preferred.

8+ years of relevant hands-on experience in Business Intelligence domain working as a Data Engineer.

Must have strong analytical skills and be able to use statistical and data analysis tools to interpret data and identify trends and patterns.

Must be strong in data collection and transformation using SQL, Python as well as analytical tools such as Power BI or Tableau.

Proficient in programming languages like Python, R, C# is a plus.

Experience with big data technologies and data pipeline such as Hadoop, Spark, Airflow, etc.

Experience working with multiple database platforms such as SQL Server, Oracle