Data Engineer
1 month ago
The Data Engineer will be responsible for designing and building modern data platforms to support data-driven decision making. The Data Engineer will execute technical implementation of data engineering and visualization projects.
Key Responsibilities- Design, implement, and develop data pipelines to collect and process large amounts of data from various sources.
- Implement data storage solutions that are scalable, secure, and efficient, such as data warehouses and databases.
- Develop and implement data validation and testing processes to ensure that data is processed accurately and efficiently.
- Automate data collection, processing, and reporting processes to minimize manual work and improve efficiency.
- Create high-quality documents to capture problem statements, requirements, solutions, and designs.
- Contribute to the development of reusable, repeatable collateral for use across the practice.
- Implement data quality checks and validation processes to ensure the accuracy, consistency, and security of data.
- Monitor data pipelines and processes, troubleshoot issues, and implement solutions to prevent recurrence.
- Maintain comprehensive documentation of data architectures, processes, and workflows to facilitate knowledge sharing and collaboration.
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- 3 to 5 years of experience in data management, data engineering, or data visualization.
- Excellent problem-solving, organization, debugging, and analytical skills.
- Ability to work independently and in a team environment.
- Excellent communication skills for effectively expressing ideas to team members and clients.
- Understanding of relational database concepts and SQL querying.
- Knowledge of cloud computing platforms, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
- Experience building data pipelines with ETL tools/Equivalent Cloud services, such as Azure Data Factory, dbt, AWS Glue, Matillion, or equivalent.
- Familiarity with data warehousing solutions, such as Amazon Redshift, Snowflake, Google BigQuery, or Azure Synapse.
- Experience with visualization tools, such as Power BI, Looker, Tableau, and QuickSight.
- Debug and optimize existing data infrastructure and processes as needed.
- Experience building large-scale, high-throughput, 24x7 data systems.
- Any data engineering, visualization, or data science certifications on any of the clouds.
- Experience with at least one programming language, such as Python, Java, or Vue.
- Exposure to machine learning algorithms, AI, and/or LLM, with implementation in practice.
- Experience with legacy data systems (e.g. Hadoop, Informatica).
- Experience in migrating data engineering workloads from on-prem to cloud or between clouds.
- Experience in GCP Data services is preferred.
Our employees multiply their potential because they have opportunities to: Create a lasting Impact, Learn and Grow professionally & personally, Experience great Culture, and Be your Whole Self
Beyond an amazing, collaborative work environment, great people, and inspiring, innovative work, we have some great benefits and perks:
- Benchmarked, competitive, in-market total rewards package including (but not limited to): base salary & short-term incentive for all employees
- Fully remote-first, small but Global organization; 'learn wherever, whenever' frees our people from a rigid view of learning and growth
- Retirement planning (i.e. CPF, EPF, company-matched 401(k))
- Globally, we build benefit plans that offer choices for whatever stage in life our employees are in and allow for flexibility as life happens.
- Employees have access to a fully comprehensive benefits package to choose the medical, dental, and vision insurance plan that best fits their lives.
- In addition to great healthcare coverage, we also offer all employees mental health resources and additional wellness programs.
- Generous time off and leave allowances
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