AddressJob Description
Lead Data Engineer
- Seeking candidates with total experience of 10+ years and 6 years into data Engineering field.
- Be an advocate with obsession for excellence delivering measurable success for Advance Auto Parts stakeholders with secure, scalable, highly available cloud architecture that leverages AWS Cloud services.
- Provides technical leadership in AWS cloud tech stack, Snowflake and any ETL tool like Talend.
- Extensive hands-on expertise in Pyspark, Airflow and RDS(Postgress).
- Capable of conceptualizing, prototyping, and articulately presenting appropriate solutions to leadership for effective decision-making.
- Ability to assess the current environment, requirements and propose Data Engineering Solutions.
- Ability to build frameworks and pipelines using AWS and PySpark.
- Skilled in crafting comprehensive solutions across AWS and Azure platforms, with demonstrated hands-on experience in design and implementation.
- Proficiency in delivering high-quality Data Engineering services is a must have for this role.
- Lead the entire lifecycle of project delivery, from development to production, and provide post-production warranty support.
- Able to work with platform team in problem solving and troubleshooting activities.
- Propose Standard and Best Practices by leveraging AWS Services.
- Apply creative thinking/approach to arrive at technical solutions that enhance business goals and align with corporate technology strategies.
- Help Application teams in onboarding the feeds into the built-in frameworks.
- Make sure to follow the best design practices during the implementation of ETL Frameworks.
- Demonstrate expertise in developing pipelines within Databricks and Airflow frameworks, ensuring meticulous attention to detail in establishing efficient monitoring, logging, and auditing capabilities.
- Responsible for conducting regular code reviews and performance evaluations to ensure high standards of quality and efficiency.
- Capable of cultivating effective collaboration with technical teams, delivery managers, as well as Data Engineers, scientists, and analysts.
Qualification:
- Bachelor’s or Master’s Degree in Computer Science or equivalent experience
- At least 10 years of experience in application design, development, and analysis
- Experience in AWS Cloud Solutions. Retail Industry experience preferred.
- Implement data transformations and data structures for data warehouse and lake/repository.
- Experience in creating Various ETL Frameworks in processing or extracting the data from cloud databases by using AWS Services by leveraging Lambda, Glue, PySpark, Step Functions, SNS, SQS and Batch.
- Having certifications in AWS, Azure, Snowflake, and Databricks is an added advantage for this position.
- Proficiency in Git, Azure DevOps, and DevOps pipelines is a valuable asset for this position.
- Proficient in Terraform for infrastructure as code, Python scripting for automation, shell scripting for system tasks, and containerization technologies. Additionally, experienced in orchestrating web services.
- Proven ability to be a strategic thinker to drive the necessary ownership and data governance within the organization.
- Ability to evaluate risks and provide business recommendations / solutions in a timely manner
- Should have sound knowledge in various AWS Services.
- Able to scan ETL Frameworks and propose optimizations and cost savings.
- In addition to technical proficiency, the candidate should possess the ability to mentor junior team members, providing guidance and support to foster their professional growth and development within the team.
- Understanding of and experience working in an Agile environment.
- Able to work with other cross functional team members, both onshore and offshore for solutions and development tasks
- Independent. Strong critical thinking, decision making, troubleshooting and problem-solving skills.
- Go-Getter. Possesses strong, planning, execution and multitasking skills and demonstrated ability to reprioritize accordingly. Must be able to manage quickly changing priorities while meeting deadlines.
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