Data Engineer

We are currently looking for Data Engineer for our Cloud and Enterprise Information
Management Practice. Develop architectural models for Cloud-based data management
solutions leveraging Microsoft Azure / AWS / GCP / Snowflake technologies to operate at
large scale and high performance.
MAIN DUTIES AND RESPONSIBILITIES
Responsible for the functional design requirements for a cloud-based Data Management
solution and design conceptual, logical, physical data models that can meet current and
future business needs.
2.

• Provides Cloud and Data Management environments, able to deep dive and

identify root cause of issues.
3.
• Evaluate and Plan DWH Migrations to Cloud.

4.
• Manage the data engineering roadmap and help to bring the organization

towards an automated, scalable and fault-tolerant infrastructure
5.
• Advance writing and building data pipelines, lakes, managing ETL processes

and perform a number of transformations.
6.
• Understanding relational and big data models to both store and access data

from data visualization and other query tools.
7.
• Build data management platforms using Cloud Technologies like Data Factory,

Data Lake, Data Bricks, Cosmos SQL, Blob, Redshift, Lambda, RDS, S3, EC2


• Experience in Data Architecture, Data Management and Analytical Technologies of

modern data platforms on Cloud.

• Experience with Extract, Transform & Load and ELT development is required


• Familiarity and good understanding of Data Models - relational and dimension models

is required

• Proven expertise in Data Modeling, Data Profiling, Data Analysis, Data Quality, Data

Governance and Data Lineage.

• Experience in leveraging Snowflake for building data lakes / data warehouses is

highly preferred.

• Excellent SQL Skills along with ETL/data processing tools such as Informatica,

Talend, Pentaho, Databricks, Spark, Alteryx.

• Experience with Snowflake utilities such as SnowSQL, SnowPipe, Python, Tasks,

Streams, Time travel, Optimizer, Metadata Manager, data sharing, and stored procedures.

• Experience in Programming Languages such as Python


• Experience in using Python Libraries for Data mining, Data Modeling and Processing

and Data Visualizations

• Experience in SQL / NO SQL Databases such as Oracle, MS SQL Server, Cassandra,

Mongo DB, HBase, Zen, Elastic Stack, Couch DB, Dynamo DB and others.

• Experience in Data Pipelines such as Kafka or Apache Airflow


• Experience in Big Data Ecosystem (Apache Hadoop, Spark, Kafka) and/or the IaaS or

PaaS Ecosystem (Microsoft Azure, Google Cloud, AWS).

• Should be strong in Azure Data Factory, Data Lake, Data Bricks, Cosmos SQL, Blob,

Redshift, Lambda, RDS, S3, EC2, Kinesis, AWS/Azure/Snowflake Data Warehouse and
other services.

• Experience in BI tools such as Tableau, Power BI.


• Experience in Continuous Integration and Delivery.


• Experience with JIRA/Confluence and source control environments like Git, GitHub

etc.

• Experience with software development in a Windows, Linux/Unix environment.


• Experience in Agile methodologies (Kanban and SCRUM).


• Ability to work autonomously and with small cross-functional teams.


• Communication skills including technical documentation, development and delivery

of demonstrations and presentations and the ability to listen and communicate effectively
with functional leaders.