Company : LT Partners
Designation : Data Engineer
Location : Work From Home
Salary : 24 LPA - 32 LPA
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field
- Experience in data engineering or related field
- Strong knowledge of advanced SQL functions such as aggregations and window functions; preferred to have background with Python or other programming languages
- Experience with data quality and validation checks, structured and unstructured data, and pipeline development preferred
- Strong problem-solving skills and ability to troubleshoot complex issues
- Excellent communication and collaboration skills
- Able to quickly learn new systems and software programs with minimal training, documentation or guidance
- Works well in a team environment, as well as independently
Responsibilities
- Must work at least 50% of hours during USA timezones (PST/PDT).
- Design, develop, and implement pipelines and integrations to connect to various client databases, as well as ingesting into a single base for our cross-client, agency-wide database.
- Normalize marketing data sources across delivery platforms, attribution and analytic sources, and client data into a common agency-standard model.
- Transform data for reporting and insights, ensuring that data is properly transformed and loaded into BigQuery via dbt.
- Develop and implement data models and conventions to create a cohesive database for analysis, including calculating KPIs, designing and applying analytic processes, and visualizing data using visualization tools such as Looker Studio, Tableau, Salesforce Datorama, etc.
- Build and maintain various DAGs for orchestration/scheduling.
- Develop and implement data quality and validation checks.
- Develop, enhance, and maintain end-user computing or semi-automated tools using tools such as Salesforce Datorama, Adverity, Python, SQL, Google BigQuery, Airtable, Google Sheets, Excel, Looker Studio, and Tableau or other relevant BI tools.
- Document data dictionary, and data model that supports the enterprise data lake.
- Respond to support requests and troubleshoot data and pipeline issues.
- Other tasks and projects as assigned.
Hiring Process
- Apply through Cuvette.tech with resume
- 2-3 phone interviews
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