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Data Engineer

About BOT Consulting

BOT Consulting enables global technology leaders to build, scale, and transition high-performing Global Delivery Centers (GDCs) with speed and precision. By integrating top talent, AI-driven innovation, and a culture-first approach, we simplify global expansion into a seamless, low-risk journey. Our proprietary Build-Operate-Transfer (BOT) model ensures GDCs are rapidly operationalized, culturally aligned, and strategically positioned for long-term success. 

We are looking for a talented and motivated Data Engineer with 3-6 years of experience to join our dynamic team. The ideal candidate will have expertise in building and maintaining data pipelines, working with large datasets, and transforming data into actionable insights. As a Data Engineer, you will play a key role in developing the infrastructure and tools necessary to support our data-driven decision-making processes and improve the overall efficiency of the business.

Candidates with experience in Private Equity or Capital Markets will be preferred.

Key Responsibilities:

  • Data Pipeline Development: Design, implement, and maintain scalable and efficient data pipelines to collect, process, and store data from various sources (structured and unstructured).

  • Data Transformation: Work with stakeholders to understand business requirements and create ETL (Extract, Transform, Load) processes that ensure high-quality and reliable data flows into data storage systems.

  • Database Management: Work with relational and NoSQL databases (e.g., SQL Server, PostgreSQL, MongoDB) to store and query large datasets. Optimize database performance and ensure efficient data storage.

  • Data Integration: Integrate data from various internal and external systems using API calls, batch processing, and other data integration methods.

  • Data Warehousing: Assist in building and maintaining data warehousing solutions (e.g., Databricks, Amazon Redshift, Google BigQuery, Snowflake) to support business intelligence and analytics needs.

  • Automation & Optimization: Automate manual data processes and workflows to streamline data operations and increase efficiency.

  • Collaboration with Data Science and Analytics Teams: Work closely with data scientists, data analysts, and other teams to ensure data is available, accurate, and usable for analytics, machine learning, and business intelligence purposes.

  • Data Quality & Governance: Implement data quality checks and data governance processes to ensure the accuracy, consistency, and integrity of data.

  • Performance Monitoring: Monitor the performance of data pipelines and databases, troubleshoot performance issues, and implement optimizations where necessary.

  • Documentation: Document data workflows, architecture, and processes for future reference and to ensure the sustainability of systems.

  • Stay Current with Emerging Technologies: Stay up to date with the latest trends and best practices in data engineering and big data technologies.



Requirements

Qualifications:

  • Experience: 3-6 years of professional experience as a Data Engineer or in a similar data-related role.

  • Technical Skills:

    • Strong proficiency in SQL and experience with both relational and NoSQL databases.

    • Hands-on experience with ETL tools (e.g., Apache Airflow, Talend, Informatica, Microsoft SSIS).

    • Experience working with big data technologies (e.g., Hadoop, Spark, Kafka) is a plus.

    • Familiarity with cloud platforms like AWS, Google Cloud Platform (GCP), or Microsoft Azure, particularly for data storage and processing.

    • Experience with data warehousing solutions (e.g., Databricks, Amazon Redshift, Google BigQuery, Snowflake).

  • Programming Skills: Proficiency in at least one programming language, such as Python, Java, or Scala, to write scripts and automate data tasks.

  • Data Modeling: Solid understanding of data modeling, including creating schemas, dimensional models, and normalized data structures.

  • Data Integration: Experience in integrating data from multiple sources, including APIs, external databases, and file-based systems (e.g., JSON, XML, CSV).

  • Problem-Solving: Strong analytical and problem-solving skills, with the ability to troubleshoot data pipeline issues and ensure data accuracy.

  • Collaboration: Excellent teamwork and communication skills to work with cross-functional teams including data analysts, data scientists, and business stakeholders.

  • Education: Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent experience).

Preferred Skills:

  • Experience with containerization technologies like Docker or Kubernetes.

  • Familiarity with DevOps practices and tools for continuous integration and deployment (CI/CD).

  • Knowledge of data visualization tools such as Tableau, Power BI, or Looker.

  • Familiarity with machine learning workflows and integrating data engineering solutions with data science pipelines.



Benefits

  • Insurance
  • Paid leave
  • Technical training and certifications
  • Robust learning and development opportunities
  • Incentive
  • Toastmasters
  • Food Program
  • Fitness Program
  • Referral Bonus Program


Full time
Jaipur
4-5 years
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