The company's Global Insights & Data business line is a market leader in data, platform, and analytics across various sectors, including financial services, consumer products, manufacturing, and life sciences. The role of Lead Data Engineer (Cloud) is crucial for driving data-driven decision-making processes within the organization. The ideal candidate will possess a blend of analytical skills and strategic foresight, coupled with the ability to collaborate across diverse teams.
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In this position, you will be responsible for:
- Designing, developing, and maintaining scalable ETL (Extract, Transform, Load) pipelines using cloud-native tools.
- Implementing best practices for data ingestion, transformation, and loading processes from multiple sources.
- Automating workflows and developing data pipelines with tools such as Apache Airflow, Glue, Databricks, or Dataflow.
- Architecting, building, and maintaining cloud-based data solutions utilizing AWS, Azure, or Google Cloud Platform (GCP).
- Optimizing cloud infrastructure for cost, performance, and security.
- Implementing monitoring, logging, and alerting solutions for data pipelines and cloud infrastructure.
Skills and Experience Required:
- Bachelor's degree in data science, analytics, business, or a related field (advanced degrees or certifications are a plus).
- Proven analytical thinking and problem-solving abilities.
- Proficiency with cloud platforms like AWS (S3, EC2, EMR, Glue, Lambda), Azure (Data Factory, Blob Storage, HDInsight), or GCP (Big Query, Dataflow, Pub/Sub).
- Strong programming skills in Python, Java, Scala, or SQL.
- Experience with big data tools (Hadoop, Spark, Kafka, etc.).
- Proficiency in ETL processes and data transformation techniques.
- Familiarity with relational and non-relational databases (PostgreSQL, MongoDB, Cassandra).
This role offers an opportunity to help clients leverage technology to innovate and grow their businesses while contributing to a sustainable and inclusive future.
