AWS Data Engineer at Mactores

Short Description:

Mactores, a leader in modern data platform solutions, seeks an AWS Data Engineer (Associate) for a full-time remote position in Mumbai. The role involves collaborating with business leads, analysts, and data scientists to develop efficient code in PySpark and Amazon Glue, and craft SQL Queries using Amazon Athena and Redshift. The ideal candidate possesses 1 to 3 years of experience in Apache Spark, PySpark, Amazon Glue, and demonstrates a deep understanding of Spark 2.7+ Dataframe API. Mactores fosters a dynamic and inclusive work culture based on 10 Core Leadership Principles, inviting individuals who thrive in a collaborative, creative, and flexible environment to join their world-class team. The recruitment process includes pre-employment assessments, managerial interviews, and HR discussions, emphasizing equal opportunities and nondiscrimination.

Position: AWS Data Engineer (Associate)

Location: Mumbai, MH (Engineering – Data Engineering and Data Science)

Employment Type: Full Time (Remote)

Mactores is a recognized leader in delivering contemporary data platform solutions to businesses. Since 2008, Mactores has empowered businesses with End-to-End Data Solutions that are automated, agile, and secure, fostering accelerated value through automation. Collaborating closely with customers, we guide them through digital transformations via assessments, migration, or modernization.

As an AWS Data Engineer, you will be a versatile data engineer adept at solving business problems. Collaborating with business leads, analysts, and data scientists, you will delve into the business domain and work alongside fellow engineers to develop data products that enhance decision-making. Your dedication to ensuring data quality in business metrics and creating flexible solutions that scale to address broader business questions is paramount.

If you possess a passion for problem-solving through your skills, we invite you to join Team Mactores. Our office environment is casual and enjoyable, avoiding a rigid "corporate" culture, emphasizing productivity, creativity, and offering the opportunity to be part of a world-class team while embracing individuality.

Responsibilities:

Write efficient code in PySpark and Amazon Glue.
Craft SQL Queries using Amazon Athena and Amazon Redshift.
Explore new technologies and employ innovative techniques to creatively solve business problems.
Collaborate with engineering and business teams to develop superior data products and services.
Collaborate with the team to deliver projects on time and provide timely updates to customers.

Requirements:

1 to 3 years of experience in Apache Spark, PySpark, Amazon Glue.
2+ years of experience in writing ETL jobs using PySpark and SparkSQL.
2+ years of experience in SQL queries and stored procedures.
Deep understanding of the Dataframe API with all the transformation functions supported by Spark 2.7+.

Preferred Qualifications:

Prior experience in working on AWS EMR, Apache Airflow.
Certifications: AWS Certified Big Data – Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer.
Understanding of DataOps Engineering.

Life at Mactores:

We prioritize creating a culture that significantly impacts the lives of every Mactorian. Our 10 Core Leadership Principles guide decision-making, leadership, collaboration, and curiosity in our work environment.

Be one step ahead
Deliver the best
Be bold
Pay attention to the detail
Enjoy the challenge
Be curious and take action
Take leadership
Own it
Deliver value
Be collaborative

Explore more about our work culture at Mactores Careers.

The Path to Joining the Mactores Team:

At Mactores, our recruitment process follows three stages:

Pre-Employment Assessment: Participate in a series of evaluations to assess technical proficiency and suitability for the role.
Managerial Interview: Engage in discussions with the hiring manager to assess technical skills, hands-on experience, leadership potential, and communication abilities.
HR Discussion: Discuss the offer and next steps with a member of the HR team during a 30-minute session.

Please click here to apply.

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