Data Engineer

Minimum of 7+ years of experience in the data analytics field.

Proven experience with Azure/AWS Databricks in building and optimizing data pipelines,

architectures, and datasets.

Strong expertise in Scala or Python, PySpark, and SQL for data engineering tasks.

Ability to troubleshoot and optimize complex queries on the Spark platform.

Knowledge of structured and unstructured data design, modelling, access, and storage

techniques.

Experience designing and deploying data applications on cloud platforms such as Azure or AWS.

Hands-on experience in performance tuning and optimizing code running in Databricks

environments.

Strong analytical and problem-solving skills, particularly within Big Data environments.

Experience with Big Data management tools and technologies including Cloudera, Python,

Hive, Scala, Data Warehouse, Data Lake, AWS, Azure.

Technical and Professional Skills:

Must Have:

Excellent communication skills with the ability to interact directly with customers.

Azure/AWS Databricks.

Python / Scala / Spark / PySpark.

Strong SQL and RDBMS expertise.

HIVE / HBase / Impala / Parquet.

Sqoop, Kafka, Flume.

Airflow.