able to work across full data cycle. - Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD - Coding experience in ApacheSpark, Iceberg or Python (Pandas) - Experience in change and release management. - Experience in Database Warehouse design and data modelling - Experience managing Data Migration projects. - Cloud data platform development … the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB - Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have) - Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of … other data tools and programming languages such as Python & Spark and Strong SQL experience. - Experience is building Data lake and building CI/CD data pipelines - A candidate is expected to understand and can demonstrate experience across the delivery lifecycle and understand both Agile and Waterfall methods and when to apply these. Experience: This position requires several years of More ❯
in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. ApacheSpark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical More ❯
requirements. In order to secure one of these Senior Data Engineer roles you must be able to demonstrate the following experience: Experience in prominent languages such as Python, Scala, Spark, SQL. Experience working with any database technologies from an application programming perspective - Oracle, MySQL, Mongo DB etc. Experience with the design, build and maintenance of data pipelines and infrastructure More ❯
best practices for data security and compliance. Collaborate with stakeholders and external partners. Skills & Experience: Strong experience with AWS data technologies (e.g., S3, Redshift, Lambda). Proficient in Python, ApacheSpark, and SQL. Experience in data warehouse design and data migration projects. Cloud data platform development and deployment. Expertise across data warehouse and ETL/ELT development in More ❯
demonstrate the following experience: Commercial experience gained in a Data Engineering role on any major cloud platform (Azure, AWS or GCP) Experience in prominent languages such as Python, Scala, Spark, SQL. Experience working with any database technologies from an application programming perspective - Oracle, MySQL, Mongo DB etc. Some experience with the design, build and maintenance of data pipelines and More ❯
