AWS Data Engineer

Job Description

We are seeking a skilled Data Engineer with over 5+ years of experience to design, build, and maintain scalable data pipelines and perform advanced data analysis to support business intelligence and data-driven decision-making. The ideal candidate will have a strong foundation in computer science principles, extensive experience with SQL and big data tools, and proficiency in cloud platforms and data visualization tools.

Responsibilities

Key Responsibilities:

Exp: 5+ years

• Design, develop, and maintain robust, scalable ETL pipelines using Apache Airflow, DBT, Composer (GCP), Control-M, Cron, Luigi, and similar tools.
• Build and optimize data architectures including data lakes and data warehouses.
• Integrate data from multiple sources ensuring data quality and consistency.
• Collaborate with data scientists, analysts, and stakeholders to translate business requirements into technical solutions.
• Analyze complex datasets to identify trends, generate actionable insights, and support decision-making.
• Develop and maintain dashboards and reports using Tableau, Power BI, and Jupyter Notebooks for visualization and pipeline validation.
• Manage and optimize relational and NoSQL databases such as MySQL, PostgreSQL, Oracle, MongoDB, and DynamoDB.
• Work with big data tools and frameworks including Hadoop, Spark, Hive, Kafka, Informatica, Talend, SSIS, and Dataflow.
• Utilize cloud data services and warehouses like AWS Glue, GCP Dataflow, Azure Data Factory, Snowflake, Redshift, and BigQuery.
• Support CI/CD pipelines and DevOps workflows using Git, Docker, Terraform, and related tools.
• Ensure data governance, security, and compliance standards are met.
• Participate in Agile and DevOps processes to enhance data engineering workflows.
  
  

Requirements

Required Qualifications:

• 5+ years of professional experience in data engineering and data analysis roles.
• Strong proficiency in SQL and experience with database management systems such as MySQL, PostgreSQL, Oracle, and MongoDB.
• Hands-on experience with big data tools like Hadoop and Apache Spark.
• Proficient in Python programming.
• Experience with data visualization tools such as Tableau, Power BI, and Jupyter Notebooks.
• Proven ability to design, build, and maintain scalable ETL pipelines using tools like Apache Airflow, DBT, Composer (GCP), Control-M, Cron, and Luigi.
• Familiarity with data engineering tools including Hive, Kafka, Informatica, Talend, SSIS, and Dataflow.
• Experience working with cloud data warehouses and services (Snowflake, Redshift, BigQuery, AWS Glue, GCP Dataflow, Azure Data Factory).
• Understanding of data modeling concepts and data lake/data warehouse architectures.
• Experience supporting CI/CD practices with Git, Docker, Terraform, and DevOps workflows.
• Knowledge of both relational and NoSQL databases, including PostgreSQL, BigQuery, MongoDB, and DynamoDB.
• Exposure to Agile and DevOps methodologies.
• Experience with Amazon Web Services (S3, Glue, Redshift, Lambda, Athena)
  
  

Nice to have

Preferred Skills

• Strong problem-solving and communication skills.
• Ability to work independently and collaboratively in a team environment.
• Experience with service development, REST APIs, and automation testing is a plus.
• Familiarity with version control systems and workflow automation.
  
  

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office
  
  

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.