Senior Data Engineer

This role presents a dynamic opportunity to work across AWS, Azure, and Google Cloud environments, contributing to meaningful initiatives and cloud-based solutions.

**Core Responsibilities and Required Skills:**

* Expertise working with AWS, Azure, and Google Cloud platforms.
* Solid background in data engineering, including designing, building, and refining data pipelines.
* Strong understanding of data modeling, ETL workflows, and data warehousing architectures.
* Experience with programming languages such as Python, Java, or Scala.
* Ability to collaborate effectively within multidisciplinary teams and help drive key projects forward.

**Additional Technical Experience:**

* Hands-on production experience with major data platforms: Snowflake, AWS, Azure, GCP, Hadoop, Databricks.
* Familiarity with cloud and distributed storage systems such as S3, ADLS, HDFS, GCS, Kudu, ElasticSearch/Solr, Cassandra, or similar NoSQL technologies.
* Proficiency with data integration and streaming tools, including Spark, Kafka, Streamsets, Matillion, Fivetran, NiFi, AWS DMS, Azure Data Factory, Informatica IICS, Google DataProc, or comparable technologies.
* Experience working with diverse data sources (queues, relational databases, file systems, search platforms, APIs).
* Full software development lifecycle exposure—design, documentation, implementation, testing, and deployment.
* Skills in automated data transformation and curation using tools like dbt, Spark, Spark Streaming, and automated pipeline frameworks.
* Knowledge of workflow orchestration tools such as Airflow, AWS Managed Airflow, Luigi, and NiFi.



Please complete these questions and send your resume.


Day to Day Key Responsibilities at current/previous role:

2 Top Projects at current job, what problem did you solve, how and why:

Do you have Consulting Experience:

What is your Python level:

What is your SQL level:

What is your Java level:

What is your Scala level:

What is your AWS level:

What is your Snowflake level:

What is your MS Azure level:

Fivetran level:

Have you completed Data engineering tasks:

Have you completed Data warehousing tasks:

Have you completed Data lakes tasks:

Have you completed ETL end to end tasks:

Have you completed Data migration tasks: