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Hiring Data Engineer & Sr. Data Engineer - Remote

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Hiring Data Engineer & Sr. Data Engineer - Remote

Access India (Triyam Information Technology)

Hiring Data Engineer & Sr. Data Engineer - Remote

Skills

SQL QueriesData EngineeringPythonAWS LambdaGitData AnalysisAWSCompliancePower BIAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Chennai, Tamil Nadu, India

Work mode:

Remote

Published on:

11 September 2026

What they need


Job Title/Role : Data Engineer, Sr. Data Engineer (Analytics & Data Products)

Mode of hire : Full-Time

Base Office Location : Guindy, Chennai

Mode of work : Remote

Shift Timing : 1:30 PM 10:30 PM IST

Experience : 4-8 Years , 8 to 10 Years

Department : Data & Analytics

Number of Positions : 5

About Us

Access is a global leader in information management solutions, offering comprehensive services across the entire document and records management lifecycle. From secure offsite storage for paper and digital records to advanced software for privacy, retention, and document management, Access enables organizations to protect, govern, and maximize the value of their information. Our end-to-end services include backfile imaging and digital delivery, scanning and digitization, business process automation, and secure destruction, purges, shredding and data archiving.

About the Role

We are seeking skilled Data Engineers / Senior Data Engineers to build, and maintain scalable platforms and pipelines that power analytics, reporting, and data products across the organization. You will develop robust ETL/ELT solutions, optimize data workflows, and enable trusted, high-quality data for business intelligence, advanced analytics, and data-driven decision-making. You will translate business requirements into robust database logic, automated data workflows, and insightful dashboards that enable data-driven decision-making across the organization. Depending on experience level, the role will contribute to solution design, development, optimization, and technical leadership within the data services team.

Roles and Responsibilities

  • Build, optimize, and manage data ingestion workflows from multiple structured and unstructured data sources.
  • Develop and optimize SQL queries, stored procedures, functions, and views for high-volume relational databases.
  • Design and maintain data models that support analytics, reporting, and data products.
  • Design, develop, and maintain scalable data pipelines using SQL, Python, and modern ETL/ELT frameworks.
  • Perform data profiling, cleansing, validation, and quality monitoring to ensure data accuracy, integrity, and consistency.
  • Optimize database and pipeline performance through indexing, partitioning, query tuning, and workload optimization.
  • Collaborate with Product Managers, and business stakeholders to understand business requirements and deliver analytics-ready data solutions.
  • Support the development and enhancement of data products by delivering reliable, scalable, and governed datasets.
  • Document data pipelines, data models, technical designs, and operational processes in accordance with data governance standards.
  • Implement best practices for data security, governance, metadata management, and compliance.
  • Contribute to automation, reusable frameworks, and continuous improvement initiatives.

Qualifications & Experience

  • Bachelors degree in computer science, Information Technology, and Engineering.
  • 4 to 10 years of strong hands-on experience in SQL development, ETL, and BI/reporting.

Required Skills & Experience

  • Strong proficiency in SQL (T-SQL / PL-SQL) with advanced query writing and performance tuning.
  • Hands-on experience with ETL/ELT tools such as SSIS, Azure Data Factory, Five Tran, AWS Glue
  • Experience with Azure Data Services, such as: Azure Data Factory, Azure Synapse, Azure Data Lake Storage (ADLS), Azure SQL Database, Microsoft Fabric.
  • Hands-on experience with AWS Data Services including AWS Lambda, S3, Athena, Lake Formation & Data Zone.
  • Strong programming skills in Python for data engineering and automation.
  • Strong data analysis skills, including data exploration, profiling, validation, KPI development, and translating business requirements into actionable insights.
  • Solid understanding data warehousing concepts, star/snowflake schemas, and dimensional modeling.
  • Experience supporting or developing data products and understanding the end-to-end data product lifecycle.

Preferred Skills:

  • Familiarity with version control (Git) and CI/CD for data pipelines.
  • Exposure Power BI, Service administration, gateways, and workspace management.
  • Understanding data privacy, retention, and governance frameworks.

Competencies:

  • Strong communication and stakeholder management skills.
  • Ability to work both independently and collaboratively in a hybrid.
  • Attention to detail and commitment to data accuracy.
  • Adaptability and eagerness to learn new tools and technologies.

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