The Role
Build and maintain cloud data platforms and ETL/ELT pipelines using Azure Data Factory, Matillion, Fivetran, Snowflake, Databricks, and SSIS. Develop SQL transformations, dimensional data models, and Python automation; manage AWS S3 data; integrate Salesforce; and support data quality, monitoring, BI, and AI/ML workloads. Collaborate with analysts and clients on requirements, track work in Jira, and document pipelines and processes.
Summary Generated by Built In
About the Role
We're looking for a Data Engineer to build and maintain the cloud data platforms that power analytics, BI, and AI/ML for our clients. You'll move raw, fragmented data into clean, reliable, query-ready form on Snowflake and Databricks — supporting everything from customer-360 dashboards to real-time decision-making.
Key Responsibilities
- Build, test, and maintain ELT/ETL pipelines using Matillion, Fivetran, and Azure Data Factory (ADF) to ingest data from databases, APIs, files, and SaaS sources.
- Develop data transformations and workloads on Snowflake and Databricks.
- Develop and maintain SSIS ETL packages and jobs for data integration and scheduled workloads.
- Configure and manage Fivetran connectors, including Salesforce integration into the data warehouse.
- Develop and optimize SQL transformations and data models for analytics and reporting.
- Work with AWS, including managing data in S3 (staging, ingestion, and storage).
- Write clean, reusable Python for data processing, automation, and pipeline logic.
- Support data quality, validation, and monitoring for downstream BI (Power BI/Tableau) and ML teams.
- Track and manage work through Jira workflows; partner with analysts and client stakeholders on requirements.
- Document pipelines, data definitions, and processes.
Must-Have Skills
- 1–3 years of hands-on data engineering experience.
- Azure Data Factory (ADF) — building and orchestrating pipelines.
- Databricks — hands-on development of transformations/workloads.
- Matillion — building ELT pipelines.
- Fivetran — configuring and managing connectors.
- Snowflake — hands-on data modeling and transformation.
- Strong SQL and solid working knowledge of Python.
- Understanding of data warehousing concepts, ETL/ELT, and dimensional modeling.
Good to Have
- Experience with SSIS packages and jobs.
- Salesforce data integration via Fivetran.
- AWS S3 experience.
- Exposure to Redshift or Synapse.
- BI tools (Power BI, Tableau).
- Familiarity with Jira workflows.
- Exposure to data for AI/ML workflows.
What We Look For
Curiosity, ownership, and a problem-solving mindset; comfort in a consulting/client-delivery environment; clear communication and a willingness to learn fast.
Skills Required
- 1-3 years of hands-on data engineering experience
- Hands-on Azure Data Factory experience building and orchestrating pipelines
- Hands-on Databricks development of transformations and workloads
- Hands-on Matillion experience building ELT pipelines
- Hands-on Fivetran experience configuring and managing connectors
- Hands-on Snowflake experience with data modeling and transformation
- Strong SQL skills
- Working knowledge of Python
- Understanding of data warehousing, ETL/ELT, and dimensional modeling
- Experience with SSIS packages and jobs
- Salesforce data integration via Fivetran
- AWS S3 experience
- Exposure to Redshift or Synapse
- Experience with Power BI or Tableau
- Familiarity with Jira workflows
- Exposure to data for AI/ML workflows
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The Company
What We Do
Techdome is a technology consultancy and IT solutions provider founded in 2020. It helps businesses modernize operations and navigate digital transformation through scalable, end-to-end services spanning planning, building, designing, developing, and launching technology solutions, alongside AI, cloud computing, automation, data engineering, machine learning, custom large language models, and cybersecurity. Its mission is to make complex technology accessible and support business growth across diverse industries and markets.
