Data Engineer

Experience: 7 + Years

As a Data Engineer, a key member in the team takes part of Enterprise Data & Analytics organization that brings engineering excellence at design, deliver, and operate the capabilities that transforms business. His key responsibilities are around creating data products and consumption capabilities that meet the needs of enterprise, analyst communities, and downstream systems that utilize data.

Responsibilities 

• Build, maintain, and deploy data products for analytics , data science teams on cloud platforms (e.g. AWS). 
• Design, build and maintain batch or real-time data pipelines in production. Partners closely with data architects to deliver in alignment with the Long term architecture of data engineering solutions.
• Maintain and optimize the data infrastructure required for accurate extraction, transformation, and loading of data from a wide variety of data sources.
• Develop ETL (extract, transform, load) processes to help extract and manipulate data from multiple sources. 
• Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures. Exposure to SOX compliance.
• Monitor data systems performance and implement optimization strategies. Improves operational practices and hence metrics.

Qualifications 

• Bachelors degree in computer science, Information Systems, or a related field. Minimum of 5+ years of relevant working experience in data engineering.
• Experience working with cloud Data Warehouse solutions (Snowflake). and Cloud-based solutions (e.g. AWS, Azure, GCP). Exposure to salesforce or any CRM.
• Experience working with data ingestion tools such as Fivetran, Talend.
• Advanced SQL skills and experience with relational databases and database design. Experience with working on large data sets and distributed computing(Spark/Hive/Hadoop)
• Strong proficiency in object-oriented languages: Python, Java. Strong proficiency in scripting languages. 
• Strong proficiency in data pipeline and workflow management tools (Airflow). 
• Excellent problem-solving, communication, and organizational skills. Proven ability to work independently and with a team.
• Is a self-starter and action biased. Strong in communications that handles stake holder communications.
• Follows agile methodology to work , collaborate and deliver in a global team set up. Ability to learn and adapt quickly.

Mandatory skills required for a Data Engineer.

• Data Engineering concepts (PySpark, NumPy, Pandas, AWS Glue and Airflow)
• SQL (basic and intermediate) exclusively Oracle hands-on work experience (SQL profilers / Query Analyzers)
• AWS cloud related (S3, RDS, RedShift)
• Data pipelines and distributed computing concepts
• ETL