Data Engineer
Job Info
Design, constructs, and maintains the systems and architectures that allow for the extraction, transformation, and loading (ETL) of large volumes of telecom data. This includes creating data pipelines, integrating diverse data sources, and ensuring the availability of high-quality data for analysis.
Responsibilities
Develop and maintain data pipelines for efficient data collection and processing.
Design and manage data warehouse solutions for storage and analysis.
Integrate data from various sources to ensure consistency and reliability.
Transform raw data into usable formats for analysis through ETL processes.
Implement data quality checks to ensure accuracy and completeness.
Design and optimise data models for scalability and performance.
Optimise data processing and storage systems for efficiency.
Ensure data security and compliance with regulatory requirements.
Collaborate with cross-functional teams to meet business requirements.
Document data engineering processes and continuously improve systems and workflows.
Skills & Knowledge
Proficiency in programming languages such as Python, Java, Scala, or SQL for data processing and manipulation.
Knowledge of data warehousing concepts and experience with technologies like Amazon Redshift, Google BigQuery, or Snowflake.
Ability to design and implement data models to support business requirements.
Familiarity with database systems for data storage and retrieval.
Understanding of big data technologies like Hadoop, Spark, or Kafka for processing and analysing large datasets.
Experience with cloud platforms like AWS, Azure, or Google Cloud Platform for deploying and managing data engineering solutions.
Knowledge of data quality principles and experience implementing data quality checks and monitoring processes.
Understanding of data security best practices and experience implementing security measures to protect sensitive data.
Strong problem-solving skills to troubleshoot data-related issues and optimise data engineering processes.
Ability to communicate effectively with stakeholders, including data scientists, analysts, and business users.
Willingness to stay updated on emerging technologies and best practices in data engineering through self-learning and professional development opportunities.
Career Progression
Junior Data Engineer - Data Engineer - Senior Data Engineer - Lead Data Engineer -Data Engineering Manager - Director of Data Engineering
Qualification Pathways
If you are looking to transfer into this role from a related role in the industry, leverage your existing experience and skills in the industry to identify transferable skills that align with a Data Engineer Role. Highlight these transferable skills on your CV and in interviews to demonstrate your suitability for positions within the sector.
If you are new to industry, follow these routes:
Step 1: Obtain a bachelor's degree in Computer Science, Information Technology, Mathematics, or a related field or apply for apprenticeships in Data Engineering.
Step 2: Acquire proficiency in programming languages such as Python or Java and databases like SQL. Familiarise yourself with data engineering concepts and tools.
Step 3: Seek internships, graduate programmes, or entry-level positions to gain practical experience working with data engineering technologies and tools.
Step 4: Consider enrolling in specialised training programmes or online courses focused on data engineering, ETL processes, big data technologies, and cloud platforms.
Step 5: Choose to pursue advanced degrees such as a Master's in Data Science, Data Engineering, or Computer Science to deepen knowledge and expertise in data engineering.
Step 6: Obtain relevant certifications such as Google Cloud Certified - Professional Data Engineer, AWS Certified Big Data - Specialty, or Cloudera Certified Data Engineer to validate skills and enhance career prospects.
Step 7: Stay updated on emerging technologies, industry trends, and best practices in data engineering through professional development opportunities, workshops, and self-study. Step 8: Build professional networks within the data engineering community to learn from peers, share knowledge, and explore career opportunities.
Step 8: After 10 years of service, you may be eligible to apply for Fellowship of The Institute of Telecommunications Professionals (ITP).
Other Info
Certifications can validate your skills to potential employers. Consider getting certified qualifications through courses such as:
Amazon Web Services (AWS) Certified Data Analytics – Specialty
Cloudera Certified Associate (CCA) Spark and Hadoop Developer
Associate Big Data Engineer
Cloudera Certified Professional Data Engineer
IBM Cloud Professional Architect
Google Certified Professional Data Engineer
SAS Certified Data Integration Developer
Relevant Apprenticeships:
https://www.instituteforapprenticeships.org/apprenticeship-standards/data-technician-v1-0
https://www.instituteforapprenticeships.org/apprenticeship-standards/data-engineer-v1-0