Job Description

Line of Service Advisory

Industry/Sector Not Applicable

Specialism Operations

Management Level Senior Associate

& Summary A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers.

This position is responsible for providing support for ETL / ELT / File Movement of data as part of an enterprise data program. The key responsibilities will be to process and move data between different compute and storage services, as well as on-premises data sources at specified intervals. The employee will also be responsible for for the creation, scheduling, orchestration and management of data pipelines.

Competency Summary

Data engineers are responsible for ensuring the availability and quality of data needed for analysis and business transactions. This includes data integration, acquisition, cleansing, harmonization and transforming raw data into curated datasets for data science, data discovery, and BI/analytics. Responsible for developing, constructing, testing and maintaining data sets and scalable data processing systems.

Data engineers work closest with Data Architects and Data Scientists. They also work with business and IT groups beyond the data sphere, understanding the enterprise infrastructure and the many source systems.

Input is raw datasets. Output is analytics-ready, integrated/curated datasets.

Key capabilities in this role family include:

• Data Acquisition - is the process of gathering and storing data in a location and format that it can be consumed for data preparation and/or downstream business uses.
• Data Preparation - is an iterative process for exploring, integrating, cleaning, validating and transforming raw data into curated datasets
• Data Publishing - is the act of releasing data in consumable form for (re)use by others.

Note: All data engineer roles should have a foundational set of knowledge in: communication, leadership, teamwork, problem solving skills, solution / blueprint definition, business acumen, architectural processes (e.g. blueprinting, reference architecture, governance, etc.), technical standards, project delivery, and industry knowledge.

Key Objectives/Deliverables

• Gather user requirements and translate them into business solutions.
• Design, develop, test, improve, and maintain new and existing solutions for data integration, data prep, ingestion, cleansing, and transforming raw data into curated datasets for business consumption.
• Incorporate deep data management expertise into solutions, including permissions, recovery, security, and monitoring.
• Validate and qualify solutions.
• Identify, troubleshoot, debug, and resolve technical issues.
• Work with business and IT groups to understand source systems and enterprise infrastructure offerings.
• Work with data from multiple data sources to build integrated views that will drive decisions
• Consult with internal customers who own the data to develop information relationships that lead to actionable insights.
• Work in Agile Sprints with business facing project teams

Minimum Position Qualifications

• Bachelor\xe2\x80\x99s Degree and 5 years\xe2\x80\x99 experience in the implementation of modern data ecosystems in AWS/Cloud platforms.
• Strong experience with AWS ETL/File Movement tools ( GLUE, Athena, Lambda, Kenesis and other AWS integration stack)
• Strong experience with Agile Development, Cloud formation Template, AWS CodeBuilt, AWS Code Pipeline
• Strong experience with Two or Three AWS database technologies ( Redshift, Aurora, RDS,S3 & other AWS Data Service ) covering security, policies, access management
• Strong programming Experience with programming language like Sql, Python and Spark
• Experience with Apache Airflow,Ansible & other automation stack.
• Excellent oral and written communication skills.
• A high level of intellectual curiosity, external perspective, and innovation interest
• Strong analytical, problem solving and investigative skills
• Experience in applying quality and compliance requirements
• Experience with security models and development on large data sets

Additional Preferences

• ITIL Certification

Mandatory Skill set-AWS Data engineer

Preferred Skill set-AWS Data engineer

Year of experience-3+

Qualifications-Btech/Mtech/M.E/B.E/MCA/MBA

Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills Data Center Engineering

Optional Skills Data Engineering

Desired Languages (If blank, desired languages not specified)

Travel Requirements Not Specified

Available for Work Visa Sponsorship? No

Government Clearance Required? No

Job Posting End Date

PwC