Data Engineering Consultant

This is a fully remote position, open to applicants in India.

📋 Description

• Contribute to client projects as a vital member of the project team.

• Aid in collecting and comprehending both business and technical requirements.

• Convert requirements into technical tasks under the guidance of senior team members.

• Assist in the creation of presentations, documentation, and project deliverables.

• Develop and support data solutions utilizing:

• Snowflake (data warehousing, data storage)

• Databricks (data processing, Spark workloads)

• AWS ecosystem (S3, Glue, Redshift, Lambda, EMR, IAM)

• Microsoft Fabric / Azure (Synapse, ADF)

• DataVault Data Automation

• Construct and maintain data pipelines (primarily batch, with some exposure to near real-time).

• Engage in ETL/ELT development and data integration tasks.

• Contribute to the creation of data platforms, including data lakes and data warehouses.

• Adhere to established best practices for coding, testing, and performance optimization.

• Assist senior team members in identifying and resolving data-related issues.

• Participate in code reviews, testing, and quality assurance processes.

• Manage assigned duties and deliver results within project timelines with minimal supervision.

• Facilitate analytics and reporting by preparing curated datasets.

• Support advanced analytics projects, including machine learning data preparation.

• Stay updated with tools, technologies, and best practices through ongoing learning.

• Assist in data governance, data quality, and documentation efforts.

• Comply with data security and regulatory standards.

• Help maintain metadata, lineage, and technical documentation.

⛳️ Requirements

• Bachelor’s degree in Data Analytics, Business Analytics, Information Systems, Computer Science, Statistics, Mathematics, Economics, or a related discipline.

• 3-5 years of experience in data engineering, analytics, or similar technical roles.

• Foundational knowledge in:

• SQL and basic data modeling principles.

• ETL/ELT processes and data integration techniques.

• Familiarity with cloud platforms such as AWS, Azure, or GCP.

• Experience with tools like Snowflake, Databricks, or comparable platforms is advantageous.

• Exposure to programming languages like Python or Scala is preferred.

• Basic understanding of contemporary data architecture concepts (data lakes, warehouses).

• Familiarity with data visualization tools (e.g., Power BI, Tableau) is a plus.

• Strong analytical and problem-solving abilities.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off

• Remote work options