We're partnering with a well-established and fast-evolving leading organization in the telecom and digital services space, known for using data at scale to enhance customer experience, drive personalization, and support business growth. With a strong focus on analytics, customer insights, and data-driven decision-making, this company is investing heavily in modern data platforms and engineering excellence.
This is a
6-month contract opportunity
to join a
Customer Lifecycle & Analytics-focused team
, where your work will directly support insights, engagement strategies, and data initiatives impacting a large customer base.
About the Role
As a
Data Engineer
, you will be responsible for designing, building, and optimizing scalable data pipelines and data platforms that support analytics, reporting, and data science initiatives. You'll work closely with data scientists, analysts, and business stakeholders to ensure high-quality, reliable, and accessible data across the organization.
Key Responsibilities
Design, build, and maintain robust ETL/ELT pipelines integrating data from multiple sources.
Develop and manage scalable data warehouse architectures to support analytics and reporting needs.
Ensure data accuracy, reliability, and availability through strong data quality checks and monitoring.
Work with large datasets using big data technologies for batch and real-time processing.
Implement data governance practices and ensure compliance with data privacy standards.
Optimize data infrastructure for performance, scalability, and cost efficiency.
Collaborate closely with analytics, data science, and business teams to enable data-driven insights.
Key Requirements
Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
3–5 years of experience in Data Engineering or a similar role.
Strong understanding of ETL processes, data warehousing concepts, and data modeling.
Hands-on experience with cloud data platforms (e.g., AWS, Snowflake).
Proficiency in SQL and experience with NoSQL databases.
Experience with big data technologies such as Hadoop, Spark, or Kafka.
Programming experience in Python or Scala.
Familiarity with ETL tools (e.g., Apache NiFi, Talend, Informatica).
Knowledge of data governance, security best practices, and privacy regulations.
Experience with version control (Git), CI/CD, and container technologies (Docker/Kubernetes) is a plus.