Data & Analytics Engineer

• This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data & Analytics Engineer based in India.
• This role offers the opportunity to design, build, and optimize modern data solutions that support business intelligence and customer-facing analytics.
• The position combines data engineering expertise with analytics development, enabling impactful insights through reliable pipelines and dashboards.
• The ideal candidate will work across engineering, product, DevOps, and customer-facing teams to deliver scalable data solutions.
• You will contribute to building and maintaining cloud-based data platforms while ensuring accuracy, performance, and data quality.
• This is a hands-on role for a professional who enjoys solving complex data challenges and translating business needs into technical solutions.
• The environment values ownership, continuous learning, collaboration, and the ability to quickly understand new products and data ecosystems.

Accountabilities

The Data & Analytics Engineer will be responsible for developing and maintaining data pipelines, analytics solutions, and reporting capabilities that enable data-driven decision-making. Key responsibilities include:

• Own dashboard delivery from development to production, including creating metrics, filters, managing refresh processes, and validating releases.
• Build and maintain batch and streaming ETL pipelines using cloud data technologies and distributed processing frameworks.
• Develop, optimize, and troubleshoot SQL queries within modern data warehouse environments.
• Support near-real-time data ingestion workflows and ensure reliable data movement across systems.
• Investigate analytics issues, identify root causes, and communicate findings effectively with technical and business stakeholders.
• Monitor data pipelines, dashboards, and workflows to ensure reliability, performance, and availability.
• Participate in incident resolution, troubleshooting activities, and root cause analysis.
• Develop strong product and business understanding to translate requirements into effective data models and analytics solutions.
• Ensure data accuracy, consistency, validation, and governance across multiple data sources.
• Collaborate with cross-functional teams to continuously improve analytics capabilities and operational processes.

Requirements

The ideal candidate is a proactive data professional with strong technical foundations in analytics engineering, cloud platforms, and data visualization. Required qualifications and skills include:

• 3-4 years of experience in data engineering, analytics engineering, or a related field.
• Strong SQL skills, preferably with experience in Redshift or similar modern data warehouse platforms.
• Solid programming experience with Python and PySpark for data processing and transformation.
• Hands-on experience with AWS data services, including S3, Glue, Redshift, and CloudWatch.
• Experience with workflow orchestration tools such as Apache Airflow, including developing, debugging, and deploying DAGs.
• Strong understanding of data modeling and data warehousing concepts.
• Experience creating BI dashboards using tools such as QuickSight, ThoughtSpot, Tableau, or Power BI.
• Ability to quickly understand new products, business contexts, and complex data structures.
• Strong problem-solving, communication, and collaboration skills.
• Ability to work independently while coordinating effectively with product, engineering, DevOps, and customer-facing teams.

Preferred qualifications include

• Experience with streaming and change data capture technologies such as Kafka, Debezium, or Spark Structured Streaming.
• Familiarity with AWS infrastructure concepts including IAM roles, security groups, Secrets Manager, Kinesis, or Firehose.
• Experience working with fintech, B2B SaaS, or customer analytics platforms.
• Strong awareness of data security, confidentiality, privacy, and responsible handling of sensitive information.

Benefits

• Fully remote work environment.
• Full-time employment opportunity.
• Opportunity to work on modern cloud-based data platforms and analytics solutions.
• Exposure to large-scale data engineering challenges and customer-facing products.
• Collaborative environment with cross-functional teams.
• Opportunities for professional growth and continuous learning.
• Ability to contribute directly to impactful data-driven initiatives.