Senior Data Engineer
Job details
About Mindcurv We help our customers rethink their digital business, experiences, and technology to navigate the new digital reality. We do this by designing sustainable and accountable solutions for humans living in a digital world. Mindcurv holistically covers the market’s need to digitalise business processes and customer experiences and take advantage of the cloud following DevOps and agile principles. We cater to the following six solution lines:
- Strategy and Advisory
- Creative Services and Digital Products
- Client Engagement Platforms
- Digital Experience and Solutions
- Data Services
- Cloud Platforms and Managed Services
- Designing, developing, optimizing, and maintaining data pipelines that adhere to ETL principles and business goals
- Solving complex data problems to deliver insights that helps our business to achieve their goals.
- Source data (structured→ unstructured) from various touchpoints, format and organize them into an analyzable format.
- Creating data products for analytics team members to improve productivity
- Calling of AI services like vision, translation etc. to generate an outcome that can be used in further steps along the pipeline.
- Fostering a culture of sharing, re-use, design and operational efficiency of data and analytical solutions
- Preparing data to create a unified database and build tracking solutions ensuring data quality
- Create Production grade analytical assets deployed using the guiding principles of CI/CD.
- You are an expert in Python, Scala, Pyspark, Pytorch, Javascript (any 2 at least) and have extensive experience in data analysis (Big data- Apache Spark environments), data libraries (e.g. Pandas, SciPy, Tensorflow, Keras etc.), and SQL.
- You are comfortable with one of the many BI tools such as Tableau, Power BI, Looker.
- You have working knowledge of key concepts in data analytics, such as dimensional modeling, ETL, reporting/dashboarding, data governance, dealing with structured and unstructured data, and corresponding infrastructure needs.
- Worked extensively in Microsoft Azure (ADF, Function Apps, ADLS), AWS (Lambda,Glue,S3), Databricks analytical platforms/tools
- Added bonus for working in cloud Data warehouses like Snowflake, Redshift or Synapse
- Certification in any one of the following or equivalent
- AWS- AWS certified data Analytics- Speciality
- Azure- Microsoft certified Azure Data Scientist Associate
- Snowflake- Snowpro core- Data Engineer
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